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Paper Citation Record · LEDGER

MVGBench: Comprehensive Benchmark for Multi-view Generation Models

As of 14 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 2 inbound Pith citation observations for arXiv:2507.00006.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.00006 v1

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:52:09.925374Z

measured 85 of 85 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T11:56:45.364984Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T21:08:58.160878Z

Reference resolution

83 of 83 outbound references displayed

  • verified exact0
  • verified fuzzy51
  • unresolved30
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07f5a463-5017-4027-98f8-b203e4503215 · outbound

This paper cites an unresolved cited work.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Unresolved cited work

Reference 1

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no resolver link, observed 2026-08-07T04:52:09.646944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.646944Z digest=sha256:4b0838d9db3c1122084e0460b01997c5a6c3f6d101b7aeb79920a229ff75fb3d

Observation bcd34ac6-ca35-4af0-a50e-1986596537a1 · outbound

This paper cites Stable zero123: Quality 3d object generation from single images.https://stability.ai/news/ stable-zero123-3d-generation, 2023.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Stable zero123: Quality 3d object generation from single images.https://stability.ai/news/ stable-zero123-3d-generation, 2023

Reference 2

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no resolver link, observed 2026-08-07T04:52:09.651465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.651465Z digest=sha256:588fdc570b0de52ecf706477fe7f7493f0522abde5caeaf2c8ed235698602da5

Observation 73ba107a-8723-4395-8aa7-be61328c9ed8 · outbound

This paper cites Met3r: Measur- ing multi-view consistency in generated images.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Met3r: Measur- ing multi-view consistency in generated images

Reference 3

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no resolver link, observed 2026-08-07T04:52:09.655543Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.655543Z digest=sha256:c95ecd1b7ae730cfcd93f9add2efc563d0b2ea9a07a8ce963fa5a043c3823931

Observation 670b4cc8-a381-46f5-bb69-90a11c1eab0a · outbound

This paper cites Ten years of pedestrian detection, what have we learned?, 2014.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Ten years of pedestrian detection, what have we learned?, 2014

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T04:52:16.333368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.659140Z digest=sha256:0e6321e62b3cf62bec7a5e66d64b09973ea04011a05cc1f5b78bfac00022a1d1

Observation bd4c3477-c936-4663-a948-8cde9b75d5ff · outbound

This paper cites Behave: Dataset and method for tracking human object inter- actions.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Behave: Dataset and method for tracking human object inter- actions

Reference 5

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raw_fallback, observed 2026-08-07T04:52:16.195302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.662915Z digest=sha256:1c87dd13c32d945a182c7d192819c919e7c9e61f7b3ea0293d4aca4d57c9bb56

Observation 6666a457-195d-4002-9b35-e5e7170a5c89 · outbound

This paper cites Align your latents: High-resolution video synthesis with la- tent diffusion models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Align your latents: High-resolution video synthesis with la- tent diffusion models

Reference 6

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raw_fallback, observed 2026-08-07T04:52:16.081643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.666711Z digest=sha256:0d6b2c1256b1c38806b5ac29f60bfc6d7fb45aa2086599ebddcb5bd303cd87e5

Observation e8f6cd43-d7dc-455d-a05e-11b2a34633df · outbound

This paper cites Muse: Text-To-Image Generation via Masked Generative Transformers.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Muse: Text-To-Image Generation via Masked Generative Transformers

Reference 7

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no resolver link, observed 2026-08-07T04:52:09.670357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.670357Z digest=sha256:bf95dec809e1d3cdc470be82b8ca7aa7c400dfec49170c76acce203321d526b5

Observation 005f3a97-b634-4d49-a3f3-1e84a622873a · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 8

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no resolver link, observed 2026-08-07T04:52:09.674558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.674558Z digest=sha256:17ffeeed6bd8a8d97590e537a39aaff108d990f896974863b1b751ac99a3c247

Observation 259b884b-2e60-46b3-9f00-db1fbb1f1000 · outbound

This paper cites V3D: Video Diffusion Models are Effective 3D Generators.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models V3D: Video Diffusion Models are Effective 3D Generators

Reference 9

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no resolver link, observed 2026-08-07T04:52:09.678640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.678640Z digest=sha256:e5e95fbad7a3b0616eeffef06d5649e24b4dc26cc380056b52543f224ec8290d

Observation 7c46d6ce-8498-401d-93ac-83103b63b85e · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 10

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no resolver link, observed 2026-08-07T04:52:09.682346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.682346Z digest=sha256:576c28be0b212363a9e405e63f7c196363218163f9abee0c52c07190691b33f8

Observation cead39f2-d64e-43fd-877c-3cf04050f09d · outbound

This paper cites Objaverse-XL: A universe of 10m+ 3d objects.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Objaverse-XL: A universe of 10m+ 3d objects

Reference 11

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raw_fallback, observed 2026-08-07T04:52:15.993385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.686138Z digest=sha256:4b5beb0fefccf5f5828d2f0c4a1b6cc15e3168dfe48ef2c4b416131d4b3aaaf8

Observation e13e1114-0a89-4428-b1dc-6184f7e25c80 · outbound

This paper cites McHugh, and Vincent Vanhoucke.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models McHugh, and Vincent Vanhoucke

Reference 12

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raw_fallback, observed 2026-08-07T04:52:15.866177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.689613Z digest=sha256:eff0d72126674c774af53f012b2cb1feef62d0b0610e8019d3ea0f7a3c6736b5

Observation 538b89ea-e8ef-41a8-a494-0f142d705270 · outbound

This paper cites Stable-edit: Text-based real image editing with stable diffusion models.https://github.com/ feizc/Stable-Edit, 2023.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Stable-edit: Text-based real image editing with stable diffusion models.https://github.com/ feizc/Stable-Edit, 2023

Reference 13

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raw_fallback, observed 2026-08-07T04:52:15.749624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.693112Z digest=sha256:14e1870151f1fe56743d01e14df6c381c19d9390fff43406b241cb7dca31b69d

Observation 98609474-f84f-4067-b4b2-9778b3d0d8fd · outbound

This paper cites CAT3D: Create Anything in 3D with Multi-View Diffusion Models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models CAT3D: Create Anything in 3D with Multi-View Diffusion Models

Reference 14

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no resolver link, observed 2026-08-07T04:52:09.696118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.696118Z digest=sha256:6b1775ba8756227bb12d6d3a72f729c84637cc92ce16efc8bed577fd0cc307e4

Observation c62bcaa6-d113-4ac6-a4a3-27d880c76c30 · outbound

This paper cites MVReward: Better Aligning and Evaluating Multi-View Diffusion Models with Human Preferences.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models MVReward: Better Aligning and Evaluating Multi-View Diffusion Models with Human Preferences

Reference 15

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unresolved
no resolver link, observed 2026-08-07T04:52:09.699469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.699469Z digest=sha256:d984b63564f88be899b848b7492cdabdb683eb00b7054714408460f1db6b811a

Observation 03b5924c-2345-480c-874c-1f1c97a482b5 · outbound

This paper cites Bop: Benchmark for 6d object pose esti- mation, 2018.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Bop: Benchmark for 6d object pose esti- mation, 2018

Reference 16

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raw_fallback, observed 2026-08-07T04:52:15.642159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.702791Z digest=sha256:5b1ea48dced8ceb3b7812cdf31dfecca1ec651c2fcd209bcb4f5658fbaf68b92

Observation 8d05ba7c-1305-456d-8180-f064355e35e8 · outbound

This paper cites MVD-Fusion: Single-view 3D via Depth- consistent Multi-view Generation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models MVD-Fusion: Single-view 3D via Depth- consistent Multi-view Generation

Reference 17

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raw_fallback, observed 2026-08-07T04:52:15.501622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.705909Z digest=sha256:8da5f549dd8f426ddf8ac34efc31dc76d8735a022acbad82e2ca6882f9a4bd70

Observation 4f4fd9e5-0efd-445d-9717-349f65904318 · outbound

This paper cites Turbo3d: Ultra-fast text-to-3d generation, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Turbo3d: Ultra-fast text-to-3d generation, 2024

Reference 18

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raw_fallback, observed 2026-08-07T04:52:15.360501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.709327Z digest=sha256:c3eebfc67d7fcee9f2f6cf4216612ee333ef516c6fb51ccb7fde53e50160d896

Observation 0e7479ef-5ddf-4c76-a54b-6f6542db6b5a · outbound

This paper cites 2d gaussian splatting for geometrically accu- rate radiance fields.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models 2d gaussian splatting for geometrically accu- rate radiance fields

Reference 19

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raw_fallback, observed 2026-08-07T04:52:15.198373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.712480Z digest=sha256:369131ab71b1ed65fd286e4f6fecf06d88926b054017b48cd7df7d22815c50a5

Observation fb38016d-5362-4aed-ac47-7d4315996eba · outbound

This paper cites TeCH: Text-guided Reconstruction of Lifelike Clothed Humans.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models TeCH: Text-guided Reconstruction of Lifelike Clothed Humans

Reference 20

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raw_fallback, observed 2026-08-07T04:52:15.077257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.715361Z digest=sha256:effe4215cb574188e75bad2d72215927449b6e0e5343fa38779c20270dde06df

Observation 087157cf-71c2-48a3-85c2-66aa2981ccce · outbound

This paper cites EpiDiff: Enhancing Multi- View Synthesis via Localized Epipolar-Constrained Diffu- sion.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models EpiDiff: Enhancing Multi- View Synthesis via Localized Epipolar-Constrained Diffu- sion

Reference 21

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raw_fallback, observed 2026-08-07T04:52:14.920282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.718365Z digest=sha256:379bc16fb91d595d7432620e5d573e2c9e391077250828e1db5f8e0016e2a64b

Observation 0e6ed58c-8801-4987-8cae-0b6bac3ae97e · outbound

This paper cites MV-Adapter: Multi-view Consistent Image Generation Made Easy.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models MV-Adapter: Multi-view Consistent Image Generation Made Easy

Reference 22

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no resolver link, observed 2026-08-07T04:52:09.721506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.721506Z digest=sha256:82a6ea4820d3b1315ae75b56b4e38e1f1da5b1d332814513c938bf58a0f09c5f

Observation 0375ac5d-5b64-440c-a248-9f13531cefe7 · outbound

This paper cites Vbench: Comprehensive benchmark suite for video generative models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Vbench: Comprehensive benchmark suite for video generative models

Reference 23

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raw_fallback, observed 2026-08-07T04:52:14.792697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.724777Z digest=sha256:69f614601890a031086c99028dce491cb0949190a4bd420d7afaa1353665ebc3

Observation 11f7a9cf-0d8a-4607-bdc0-b409369d6bb1 · outbound

This paper cites Re- thinking fid: Towards a better evaluation metric for image generation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Re- thinking fid: Towards a better evaluation metric for image generation

Reference 24

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raw_fallback, observed 2026-08-07T04:52:14.624539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.727987Z digest=sha256:571130541c895840f5f533eaa699d85fb66912cc90bd7a86e85cca9aa9a12d8c

Observation 9cab5f26-9bda-458a-bf33-aa419ed0c4bc · outbound

This paper cites NVS-Adapter: Plug-and-Play Novel View Syn- thesis from a Single Image, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models NVS-Adapter: Plug-and-Play Novel View Syn- thesis from a Single Image, 2024

Reference 25

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raw_fallback, observed 2026-08-07T04:52:14.524507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.731292Z digest=sha256:7fc1216c962d14d67655b4b1bb567866cc7a00f2e1af961d5d60bfe255df29b8

Observation 3cca4f19-daa1-4749-ba32-6e3f570bb49e · outbound

This paper cites SPAD: Spatially Aware Multi-View Diffusers.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models SPAD: Spatially Aware Multi-View Diffusers

Reference 26

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raw_fallback, observed 2026-08-07T04:52:14.395498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.734290Z digest=sha256:0db0bc587a52f66d365bb28e24e8838261b83e212df6dd5a735e2a3b23b0c3c5

Observation a626a081-26ec-49f5-8a0e-f3338a8cba3d · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42 (4), 2023.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42 (4), 2023

Reference 27

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raw_fallback, observed 2026-08-07T04:52:14.295274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.738088Z digest=sha256:e212925701c24c31dbcb31710024c20d30235b2364acdcd07cbd3cef4632c574

Observation d987eec7-311b-4b1a-96b2-4f71aab75c4f · outbound

This paper cites EscherNet: A Generative Model for Scalable View Synthesis.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models EscherNet: A Generative Model for Scalable View Synthesis

Reference 28

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raw_fallback, observed 2026-08-07T04:52:14.142232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.741188Z digest=sha256:e632bf9306bbeea8ff620278567d7c0aaf766ac2d6f5522b4d03a4fd151ce4a7

Observation a668254a-5a51-4fee-b73d-efeac63360c5 · outbound

This paper cites Imagenhub: Standardiz- ing the evaluation of conditional image generation models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Imagenhub: Standardiz- ing the evaluation of conditional image generation models

Reference 29

Resolution
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raw_fallback, observed 2026-08-07T04:52:14.000971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.744233Z digest=sha256:1e2fb18fe6d47c6829ef40c3889185fb3ed49ac5b1914e8b56863d76d744ddb2

Observation 356b43e8-c7a0-48a0-9ca0-ab786857543e · outbound

This paper cites ViVid-1-to-3: Novel View Synthesis with Video Diffusion Models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models ViVid-1-to-3: Novel View Synthesis with Video Diffusion Models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:13.858495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.747245Z digest=sha256:87c0de179d344ed387ec910afa932f181dd2e4c0eff0f9016a2ad893dc34edff

Observation 14bf7651-0e7a-448f-b7cb-d20986a55cda · outbound

This paper cites Nvcomposer: Boosting generative novel view synthesis with multiple sparse and unposed images, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Nvcomposer: Boosting generative novel view synthesis with multiple sparse and unposed images, 2024

Reference 31

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raw_fallback, observed 2026-08-07T04:52:13.738195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.750406Z digest=sha256:08dfe0c2a4d53d060b9183087ca2d6ea2b02a7cdbd077f6a23f19c6e63074e2e

Observation ce0e91ef-158e-43e9-9cfc-29f202a77391 · outbound

This paper cites Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.753634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.753634Z digest=sha256:d0cfdb7d2c71ca145bfe26408731c4257df1750ae3df6f834e0ef6aba7aa5fb7

Observation d8307f31-22ea-4072-b617-624e62537a44 · outbound

This paper cites Evaluation of text-to-video generation models: A dy- namics perspective.Advances in Neural Information Pro- cessing Systems, 37:109790–109816, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Evaluation of text-to-video generation models: A dy- namics perspective.Advances in Neural Information Pro- cessing Systems, 37:109790–109816, 2024

Reference 33

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raw_fallback, observed 2026-08-07T04:52:13.525261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.757342Z digest=sha256:016d32e955a9b8696edd36123404b8cfb94bf3bb69f6aaa7c4c5364923677c4d

Observation aa8011e9-cd77-465a-807f-49295eba958d · outbound

This paper cites an unresolved cited work.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-07T04:52:13.395020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.760544Z digest=sha256:59f3bcbd6ae6b189fd9381f16a61b7f0ee217a58c440c780264a72e487629b19

Observation 4aa29018-1af6-4bae-a609-701f8d552568 · outbound

This paper cites Stylerf: Zero-shot 3d style transfer of neural radiance fields.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Stylerf: Zero-shot 3d style transfer of neural radiance fields

Reference 35

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raw_fallback, observed 2026-08-07T04:52:13.307798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.763883Z digest=sha256:b2b5bfd0f856b8cff210854470af3157f68724859041befd7b5c6d7bc99b6341

Observation ff6e5c52-2520-42df-ab38-29ae10dadb34 · outbound

This paper cites One-2-3-45: Any Single Im- age to 3D Mesh in 45 Seconds without Per-Shape Optimiza- tion.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models One-2-3-45: Any Single Im- age to 3D Mesh in 45 Seconds without Per-Shape Optimiza- tion

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T04:52:13.157230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.767008Z digest=sha256:b0ac3189e87e57acf304f2eb13e71618358f5ef5e06407a3f5015764a53f71c6

Observation 29a15dc2-dc23-4864-9473-f8615db6d384 · outbound

This paper cites Zero-1-to-3: Zero-shot one image to 3d object, 2023.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Zero-1-to-3: Zero-shot one image to 3d object, 2023

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:13.085464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.770064Z digest=sha256:a33af74dae9b2d4933710093caa2c8e1b6253cce8cda13b4816f8db60e608432

Observation 96c411e3-cb43-42ed-9506-1aa433a61ff0 · outbound

This paper cites SyncDreamer: Generating Multiview-consistent Images from a Single-view Image.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models SyncDreamer: Generating Multiview-consistent Images from a Single-view Image

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.773092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.773092Z digest=sha256:c20863257f135f016237e00e410d4dc93d1a0a7c860c63b3aee79c81107fe51c

Observation f76af625-eb5f-4fa7-918f-1a87fbb6f14a · outbound

This paper cites Wonder3D: Single Image to 3D using Cross-Domain Diffusion.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Wonder3D: Single Image to 3D using Cross-Domain Diffusion

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.776354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.776354Z digest=sha256:d2856614199596710ff79ba24174f1681d89497ce8bd329095b6c33efd069d8e

Observation 3f5c1d3d-a0f7-464b-90a8-0da21d4a60a6 · outbound

This paper cites Direct2.5: Diverse text-to-3d generation via multi-view 2.5d diffusion.Computer Vision and Pattern Recognition (CVPR), 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Direct2.5: Diverse text-to-3d generation via multi-view 2.5d diffusion.Computer Vision and Pattern Recognition (CVPR), 2024

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.941074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.779651Z digest=sha256:574b4049377075cf3538db1ed6b1efbac9b6512fd0e59b37c8a5f3e61c245a23

Observation 6431dcbc-9ea4-4218-af09-bb19a203ec9d · outbound

This paper cites Taming 3dgs: High-quality radiance fields with limited resources.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Taming 3dgs: High-quality radiance fields with limited resources

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.805101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.782769Z digest=sha256:2619140cd596347d2ba0f4b9bee017c4cf5f5c5c222184e745b88325ca1ae7f3

Observation a9cd3ca1-d5d9-4a36-a55b-e12c2fad14bd · outbound

This paper cites Dinov2: Learning robust visual features with- out supervision, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Dinov2: Learning robust visual features with- out supervision, 2024

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.679596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.785999Z digest=sha256:98801e3c6947a4a2bd7ce94ace8159dc2aef4a5a7e258536cc00b12a176dd9c7

Observation 3cc043e4-7a97-4516-af77-0f3a3dc3db06 · outbound

This paper cites Barron, and Ben Milden- hall.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Barron, and Ben Milden- hall

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.789142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.789142Z digest=sha256:18ae7e6ff0b9d69bf64eee37f83f86dd60d4498d44bf54a69497840625712f69

Observation 52a8560c-7913-4209-8e26-68f87cd61309 · outbound

This paper cites Learning transferable visual models from natural language supervision.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Learning transferable visual models from natural language supervision

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.592403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.792374Z digest=sha256:4d297277729469ec14c64c91ff27ffbd5e6b209408ae28470961879137da9f10

Observation 450b60b1-2c2a-46fe-9af6-594c35db8076 · outbound

This paper cites Com- mon objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Com- mon objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.496250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.795648Z digest=sha256:c8e24739b68cb1ac37cc707cd4b8f025a85f13e5820bdba19e880d5df0caa5e5

Observation fcd27e52-1447-4323-ab09-616e431ae853 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models, 2021.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models High-resolution image syn- thesis with latent diffusion models, 2021

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.398911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.799008Z digest=sha256:3186ea773312093bb44dcd95b9c33e7832b5187e50cd65bd9f752dc81d6adfbb

Observation bfda15ec-31e6-48f0-bacb-3d0e45f248c7 · outbound

This paper cites Stable diffusion 3.5: High- resolution image synthesis with latent diffusion models.Sta- bility AI, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Stable diffusion 3.5: High- resolution image synthesis with latent diffusion models.Sta- bility AI, 2024

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.320946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.802102Z digest=sha256:cb80e2776abb3f0514edeb8ed68c1f3c15787a2926c72df02929bf44d5288786

Observation 623a4dd5-9200-4af5-a902-587c876a1f95 · outbound

This paper cites Zero123++: a single image to consistent multi-view dif- fusion base model, 2023.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Zero123++: a single image to consistent multi-view dif- fusion base model, 2023

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.250246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.805449Z digest=sha256:12b60a8df2fd6bb1fe26627ee944b932089e9efb87a5a535b548fa17ea07fe80

Observation 3b15a5e3-5a06-49b0-b33c-f6ea7814e8f7 · outbound

This paper cites MVDream: Multi-view Diffusion for 3D Generation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models MVDream: Multi-view Diffusion for 3D Generation

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.808682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.808682Z digest=sha256:05afc8ec6434d03a9ebe63efc97241e2fab08a2f4eeb749ff14e47904151fbe0

Observation 6c0ac041-8d5a-4234-bfd8-7cfac9729f00 · outbound

This paper cites DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.812158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.812158Z digest=sha256:1b9bc7d1492eecebbc7738293bc6482e192cc81757ca8cf0e0f4b308aa7eac51

Observation 6ff5f4fd-08c7-48cb-9bdf-06843f543fee · outbound

This paper cites an unresolved cited work.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:52:12.183406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.815698Z digest=sha256:310f198f552c4eff623724d94489585628aca7cee7a66baa89b3c8e76658477a

Observation a4baefa7-6a03-4357-8ebb-ca21f60aff70 · outbound

This paper cites LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.818903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.818903Z digest=sha256:8b8343942e87db75d730557645a8e138d8c335531fe7c732eb38a321a2cde2a9

Observation 18734df5-21af-4423-b611-b1de76025f01 · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.093788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.822473Z digest=sha256:1a7e03d1f70646072905f3233a1a4ad8ab189a03b898995c30f929ffe51fc701

Observation 757d9280-66da-4579-b2a4-2662484b9058 · outbound

This paper cites SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using La- tent Video Diffusion, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using La- tent Video Diffusion, 2024

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:12.022023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.825753Z digest=sha256:616e942adda8f8da84338e92b175d65d9873c5299c8717f738c40fb6cea41790

Observation 3063b065-80ae-431c-99fe-b3de3affb767 · outbound

This paper cites Exploiting Diffusion Prior for Real-World Image Super-Resolution.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Exploiting Diffusion Prior for Real-World Image Super-Resolution

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.828918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.828918Z digest=sha256:223bda6d284b8cc38856aa87b88e2a92e89e38555b7aeb25415b6816b2373636

Observation 5dbbb5b0-97ab-4c2e-93cf-71a65e1a0a76 · outbound

This paper cites ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.832371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.832371Z digest=sha256:ae0e08b3c9a2630ad48c63004feb254ed0b066428546f302fa4e54caedc91326

Observation bb30b1cb-b8af-4a00-be0f-e100caf1e709 · outbound

This paper cites ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.835866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.835866Z digest=sha256:3a485fef0a162d305189a97b08c856a8f3e31ea356c3e6b5085137a37422ce34

Observation b641f6fa-3065-4124-84a1-8f8940de0515 · outbound

This paper cites Novel View Synthesis with Diffusion Models,.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Novel View Synthesis with Diffusion Models,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:11.941707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.839385Z digest=sha256:afa5418e68ab247d4e080282e657d9a8dece87f27580533bbccd6bbb14ed2040

Observation d6bbc16f-a727-4250-a1f4-4c74e3d8f231 · outbound

This paper cites ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.842949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.842949Z digest=sha256:bc67260029a2b00b1f10d2055a7efa415dd54a2b5f97f97a691c5d7f501e2713

Observation 2e7b8d2f-22e0-413c-a415-390573312455 · outbound

This paper cites Direct and explicit 3d generation from a single image, 2024.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Direct and explicit 3d generation from a single image, 2024

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:11.863510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.846303Z digest=sha256:6df58a22bf991e0d0f6f533507de3480dc28e66eb2eacd977e1eee5af87c5a17

Observation c5d91cb0-e327-4d7d-9416-8baf96ab28c7 · outbound

This paper cites Direct and Explicit 3D Generation from a Single Image,.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Direct and Explicit 3D Generation from a Single Image,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:11.799702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.849412Z digest=sha256:f7f6edca6c59007304f1fb10f01310bc5e059cf5cc83286025eb2bdc63ba8877

Observation 581c67f5-561b-4fc6-8546-2f7f96329e79 · outbound

This paper cites One-Step Effective Diffusion Network for Real-World Image Super-Resolution.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models One-Step Effective Diffusion Network for Real-World Image Super-Resolution

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.852582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.852582Z digest=sha256:927a9b0b0fc61bf8d675141f0b71385ba299b3c37b20a170c3f549f88333714f

Observation 1d5d7b8a-e8e2-4a8a-abcd-12b6f943b309 · outbound

This paper cites Omniobject3d: Large-vocabulary 3d object dataset for realistic perception, reconstruction and generation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Omniobject3d: Large-vocabulary 3d object dataset for realistic perception, reconstruction and generation

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:11.701333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.855997Z digest=sha256:ce429d1464bce450387a64c9c66dc053fbbf8c5dcb85b4625439a745f16fd1ed

Observation 2d00a9ea-9850-43f2-9231-d8b072561aea · outbound

This paper cites Gpt- 4v(ision) is a human-aligned evaluator for text-to-3d genera- tion.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Gpt- 4v(ision) is a human-aligned evaluator for text-to-3d genera- tion

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:11.623596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.858951Z digest=sha256:5b564b8110993eb2a07cd4dcfa53526823b554fbfd29d2997cb5a3637d86c5d5

Observation 44a2b431-ba72-435f-84b9-c372032fe419 · outbound

This paper cites an unresolved cited work.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:52:11.525398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.862161Z digest=sha256:3396d969c93d3c7fdde8301275d4aa347800513b27c4f2db3489d7538b61f6cb

Observation d1489c1e-691b-4614-86c3-0d641f638c28 · outbound

This paper cites DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.865277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.865277Z digest=sha256:1ea3d090efa39f242c980aa93edecf09a452879bc37f721e0f23aba741e56957

Observation 8a6e81b5-b1f5-45b8-b034-e4ea3d3eabba · outbound

This paper cites CamCo: Camera- Controllable 3D-Consistent Image-to-Video Generation,.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models CamCo: Camera- Controllable 3D-Consistent Image-to-Video Generation,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:11.438073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.868914Z digest=sha256:4750c864ffc7292858b35a14b1ef3c9c492d1e2962abb7b08886e4980e426608

Observation ccf0ee6c-a93f-4c58-a0d3-999fa66bb047 · outbound

This paper cites Imagere- ward: Learning and evaluating human preferences for text- to-image generation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Imagere- ward: Learning and evaluating human preferences for text- to-image generation

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:52:11.385790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:52:09.872035Z digest=sha256:8a5c678d51590bfb396dc0fe2dcbb7a1e5956746cf6c4253aada90e747e6826f

Observation c671bd5d-f928-46cd-bd47-fb6494221f90 · outbound

This paper cites InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T04:52:09.875547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:52:09.875547Z digest=sha256:4cc8bed2523b3a3bc3808aea496febd46d3f5c500a0eee783d45051f64c98ab8

Observation 4e4585dc-c58a-4e32-b7a2-2e7d5575d75f · outbound

This paper cites Pons-Moll.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Pons-Moll

Reference 70

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Observation dfa1ac66-f9b8-4a5f-8621-22cfb00fb023 · outbound

This paper cites Human 3diffusion: Realistic avatar creation via explicit 3d consistent diffusion models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Human 3diffusion: Realistic avatar creation via explicit 3d consistent diffusion models

Reference 71

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Observation 2cb2042f-4034-400d-a5f2-031ddc129da9 · outbound

This paper cites Hi3d: Pursuing high- resolution image-to-3d generation with video diffusion mod- els.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Hi3d: Pursuing high- resolution image-to-3d generation with video diffusion mod- els

Reference 72

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Observation a37b35df-19e9-401d-b99e-ab7feea9bc07 · outbound

This paper cites Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization

Reference 73

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Observation c01b3e0f-8041-4d66-be67-f9998173d727 · outbound

This paper cites ViewFusion: Towards Multi-View Consistency via Interpolated Denoising.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models ViewFusion: Towards Multi-View Consistency via Interpolated Denoising

Reference 74

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Source-reported events for the cited work

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Observation 21ab38a3-16b1-4d93-8797-94ca4f500fef · outbound

This paper cites Mvimgnet: A large-scale dataset of multi-view images.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Mvimgnet: A large-scale dataset of multi-view images

Reference 75

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Source-reported events for the cited work

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Observation 30cd5c4f-1d09-4905-ab74-343b89edac5f · outbound

This paper cites Mip-splatting: Alias-free 3d gaussian splat- ting.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Mip-splatting: Alias-free 3d gaussian splat- ting

Reference 76

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Source-reported events for the cited work

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Observation 89eb2374-384a-4aa0-b34d-2915985249d0 · outbound

This paper cites Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenes.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenes

Reference 77

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3c3a7a24-0d06-4d5d-85bc-d7f4ac5714d9 · outbound

This paper cites Adding Conditional Control to Text-to-Image Diffusion Models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Adding Conditional Control to Text-to-Image Diffusion Models

Reference 78

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c3749e16-4b46-4bde-95da-7fa30fe20c55 · outbound

This paper cites Diffcollage: Parallel generation of large content with diffusion models.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Diffcollage: Parallel generation of large content with diffusion models

Reference 79

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cb396a53-5c5f-4c99-955b-48bda98cfde1 · outbound

This paper cites Free3D: Consis- tent Novel View Synthesis Without 3D Representation.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Free3D: Consis- tent Novel View Synthesis Without 3D Representation

Reference 80

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9d22cab8-edfc-4106-a008-f20df7948df5 · outbound

This paper cites What is the main color(s) of this object? simply answer the color(s), summarize to less than 4 colors.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models What is the main color(s) of this object? simply answer the color(s), summarize to less than 4 colors

Reference 81

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 860b3992-1b4d-4081-ac05-1fa9928cc169 · outbound

This paper cites 6 (GSO [12]), Tab.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models 6 (GSO [12]), Tab

Reference 82

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Observation ce03becb-ce71-45c7-9176-e05e2c6bc21d · outbound

This paper cites Despite robust to various settings, there are still limita- tions of our benchmark.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models Despite robust to various settings, there are still limita- tions of our benchmark

Reference 83

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Pith citing papers

Observation fe79b691-35f1-4677-9a14-59bfd28e70b1 · inbound

Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation cites this paper.

Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation MVGBench: Comprehensive Benchmark for Multi-view Generation Models

Reference 73

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation fb32d20a-9f3b-4313-b653-f6660b17cede · inbound

A Cross-Model VLM-Judge Protocol for Single-Image 3D Mesh Quality (and Why Cheap Proxies Fall Short) cites this paper.

A Cross-Model VLM-Judge Protocol for Single-Image 3D Mesh Quality (and Why Cheap Proxies Fall Short) MVGBench: Comprehensive Benchmark for Multi-view Generation Models

Reference 6

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arxiv_id, observed 2026-07-03T21:08:58.162599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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