Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards | Paper Citation Record

Observation 5e7f1dc6-b753-4395-ad33-4df42431bb48 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Training Diffusion Models with Reinforcement Learning

Reference 1

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Observation c08734c4-9597-4d29-9797-8282add0d045 · outbound

This paper cites Chan, Connor Z.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Chan, Connor Z

Reference 2

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Observation f5862024-c232-489c-a941-7a1f4f7f3db1 · outbound

This paper cites LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes

Reference 3

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Observation e10266f6-bba4-4753-aefb-184f096f109f · outbound

This paper cites Directly Fine-Tuning Diffusion Models on Differentiable Rewards.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Directly Fine-Tuning Diffusion Models on Differentiable Rewards

Reference 4

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Observation 56dc665e-ac8b-40cf-82e9-28db11c1e86b · outbound

This paper cites Objaverse: A universe of annotated 3d objects.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Objaverse: A universe of annotated 3d objects

Reference 5

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Observation cc40519e-4f1a-4efb-94b9-585c908972ff · outbound

This paper cites Optimizing DDPM Sampling with Shortcut Fine-Tuning.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Optimizing DDPM Sampling with Shortcut Fine-Tuning

Reference 6

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Observation 75aa81c1-da10-4f9a-82bd-3d1fc85bffb7 · outbound

This paper cites Re- inforcement learning for fine-tuning text-to-image diffusion models.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Re- inforcement learning for fine-tuning text-to-image diffusion models

Reference 7

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Observation 8ba3b5b2-cd96-4052-b696-4f61f9dceafd · outbound

This paper cites Get3d: A generative model of high quality 3d tex- tured shapes learned from images.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Get3d: A generative model of high quality 3d tex- tured shapes learned from images

Reference 8

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Observation 5580a1c5-694e-4a2b-98a0-f3ce55c3f421 · outbound

This paper cites Generative adversarial nets.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Generative adversarial nets

Reference 9

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Observation 6fb6cb06-cfe7-442f-bb3e-fe1ca67cb4df · outbound

This paper cites Memory-efficient backpropagation through time.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Memory-efficient backpropagation through time

Reference 10

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Observation 072ccb9e-cdea-4a8c-849c-7a8c83e73576 · outbound

This paper cites Stylenerf: A style-based 3d aware generator for high- resolution image synthesis.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Stylenerf: A style-based 3d aware generator for high- resolution image synthesis

Reference 11

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Observation 9337ba4c-572a-44ef-a580-ecab9e4347ca · outbound

This paper cites Denoising dif- fusion probabilistic models.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Denoising dif- fusion probabilistic models

Reference 12

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Observation 84603244-b2d6-4f60-9b7f-13aba364b202 · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards LoRA: Low-rank adaptation of large language models

Reference 13

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Observation aa1117db-bbd9-42f2-8f49-46eb1962cbfb · outbound

This paper cites Holopix50k: A large-scale in-the-wild stereo image dataset.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Holopix50k: A large-scale in-the-wild stereo image dataset

Reference 14

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Observation 09d9c4ac-60cf-4870-b982-db0e9e14833d · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards 3d gaussian splatting for real-time radiance field rendering

Reference 15

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Observation 587135ab-a3bc-4129-9e3f-6a390dbf39bf · outbound

This paper cites Auto-Encoding Variational Bayes.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Auto-Encoding Variational Bayes

Reference 16

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Observation a0e6cadf-287d-47ea-86da-9f5f83dcd389 · outbound

This paper cites Simple and effective synthesis of in- door 3d scenes.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Simple and effective synthesis of in- door 3d scenes

Reference 17

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Observation d20dba0b-b176-43fb-92b1-df5af85f7288 · outbound

This paper cites Aligning Text-to-Image Models using Human Feedback.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Aligning Text-to-Image Models using Human Feedback

Reference 18

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Observation 2a665ea9-1c54-40a1-a82a-c1642abf622f · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation, 2022.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation, 2022

Reference 19

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Observation b568713c-6ad3-40a6-94be-458629c42f9e · outbound

This paper cites Practical stereo matching via cascaded recurrent net- work with adaptive correlation.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Practical stereo matching via cascaded recurrent net- work with adaptive correlation

Reference 20

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Observation dec7405e-8328-4537-a29c-46b7d46ab2af · outbound

This paper cites Instant3d: Fast text-to-3d with sparse-view generation and large reconstruction model.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Instant3d: Fast text-to-3d with sparse-view generation and large reconstruction model

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:20.879606Z

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Observation 7f2fb560-57e4-4e5f-bf90-1f29422ae6e0 · outbound

This paper cites Synthesizing light field from a single image with variable mpi and two network fusion.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Synthesizing light field from a single image with variable mpi and two network fusion

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:20.777348Z

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Observation 3abc188c-3671-4274-a720-03bb72326e6c · outbound

This paper cites Visual instruction tuning, 2023.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Visual instruction tuning, 2023

Reference 23

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Observation 5db7cec2-d0f3-4f5f-9dfd-10688a2fa6c4 · outbound

This paper cites Mayer, E.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Mayer, E

Reference 24

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Observation 2a04e751-fa8f-49c2-8783-2cbcd12e34cb · outbound

This paper cites Realfusion: 360deg reconstruction of any object from a single image.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Realfusion: 360deg reconstruction of any object from a single image

Reference 25

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Observation 56d22d6c-59f2-4a58-8855-2b8eb7ff1484 · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Srinivasan, Matthew Tancik, Jonathan T

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:20.445689Z

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Observation c7061a66-3ba8-4018-b33b-b0edb8fe61a4 · outbound

This paper cites Giraffe: Represent- ing scenes as compositional generative neural feature fields.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Giraffe: Represent- ing scenes as compositional generative neural feature fields

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:20.241359Z

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Observation 78a7c1f4-3a94-48ef-ae01-17ee63d449a5 · outbound

This paper cites Text2Immersion: Generative Immersive Scene with 3D Gaussians.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Text2Immersion: Generative Immersive Scene with 3D Gaussians

Reference 28

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Observation 656f6c67-32fb-4ef9-93d8-404b6a3e9e2d · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards DreamFusion: Text-to-3D using 2D Diffusion

Reference 29

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Observation b9bc263d-8b48-4040-a745-e44fbab45408 · outbound

This paper cites Aligning Text-to-Image Diffusion Models with Reward Backpropagation.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Aligning Text-to-Image Diffusion Models with Reward Backpropagation

Reference 30

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Observation 5567a0da-198f-4012-a052-887566e70445 · outbound

This paper cites Sinmpi: Novel view synthesis from a single image with expanded multiplane images.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Sinmpi: Novel view synthesis from a single image with expanded multiplane images

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:20.055906Z

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Observation 53bcd4f2-e8b5-4ef2-b2f5-4e36a834b634 · outbound

This paper cites Learning transferable visual models from natural language supervision, 2021.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Learning transferable visual models from natural language supervision, 2021

Reference 32

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Observation 57c0c837-2dff-4e36-bdf2-fb7872696c7b · outbound

This paper cites Pixel- synth: Generating a 3d-consistent experience from a single image.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Pixel- synth: Generating a 3d-consistent experience from a single image

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:19.882107Z

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Observation ed603ddf-45a1-4ec8-add5-798a4c1737af · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards High-resolution image synthesis with latent diffusion models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:19.799235Z

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Observation 4300fc70-d05d-4704-b91b-6f17d100e990 · outbound

This paper cites Graf: Generative radiance fields for 3d-aware im- age synthesis.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Graf: Generative radiance fields for 3d-aware im- age synthesis

Reference 35

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Observation 7a041515-9c22-410d-b8ad-7efdcb0da8eb · outbound

This paper cites A picture is worth a thousand words: Principled recaptioning improves image generation, 2023.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards A picture is worth a thousand words: Principled recaptioning improves image generation, 2023

Reference 36

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Observation 30ae21dc-603c-4f37-9d56-b29c612cb18d · outbound

This paper cites Layered depth images.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Layered depth images

Reference 37

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Observation f75a0c57-795f-484d-bbc4-34ebac647109 · outbound

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

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards MVDream: Multi-view Diffusion for 3D Generation

Reference 38

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Observation 977f89d0-def0-461c-ae00-1f8a3bdd8d84 · outbound

This paper cites 3d photography using context-aware layered depth inpainting.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards 3d photography using context-aware layered depth inpainting

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:19.125686Z

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Observation 8cb603b3-9315-446f-812a-c81af406323a · outbound

This paper cites Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs

Reference 40

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Observation b4f21334-62fa-46fc-a48c-14ce6fadd5f2 · outbound

This paper cites Pushing the boundaries of view extrapolation with multiplane images.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Pushing the boundaries of view extrapolation with multiplane images

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:18.922764Z

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Observation 1838df48-0998-4db8-8416-dac5e88e2509 · outbound

This paper cites DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 42

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Observation 63a3bf52-867a-4ea0-8e52-ad1308315770 · outbound

This paper cites Nerf-supervised deep stereo.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Nerf-supervised deep stereo

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:18.821665Z

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Observation a18aad62-cddf-4178-8e0f-e06beaa97ea7 · outbound

This paper cites Single-view view syn- thesis with multiplane images.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Single-view view syn- thesis with multiplane images

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:18.656490Z

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Observation e1cb72ef-26d7-4f93-8940-60af1b4f43ae · outbound

This paper cites Layer-structured 3d scene inference via view synthesis.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Layer-structured 3d scene inference via view synthesis

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:18.433562Z

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Observation d7a16b7b-a1d2-49e1-b263-bab335b07fb5 · outbound

This paper cites Stereodiffusion: Training-free stereo image generation using latent diffusion models.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Stereodiffusion: Training-free stereo image generation using latent diffusion models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:18.232508Z

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Observation ebcd2c11-aba5-41fb-9988-8ce820c8fad6 · outbound

This paper cites Sea-raft: Simple, efficient, accurate raft for optical flow.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Sea-raft: Simple, efficient, accurate raft for optical flow

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Observation e2622a72-0b19-410c-be43-eb8ffe3c8a9e · outbound

This paper cites Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion

Reference 48

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Observation 4a889d05-62d7-4826-8769-e3a274411cff · outbound

This paper cites Synsin: End-to-end view synthesis from a sin- gle image.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Synsin: End-to-end view synthesis from a sin- gle image

Reference 49

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Observation c875aded-859f-48b0-ae22-7e7b413712ab · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 50

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Observation 08082198-415c-48ef-a9a8-120880e38d0a · outbound

This paper cites an unresolved cited work.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Unresolved cited work

Reference 51

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Observation 4121c58c-8de7-4b1a-8e90-3633c416a4fe · outbound

This paper cites Depth any- thing v2, 2024.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Depth any- thing v2, 2024

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:17.625627Z

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Observation d2113044-d5c3-4b2a-a093-b4ff7fc63f3a · outbound

This paper cites Wonderjourney: Going from anywhere to everywhere.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Wonderjourney: Going from anywhere to everywhere

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:17.315093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5953681b-cf7b-4760-9857-e85a6c722ebc · outbound

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

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Mvimgnet: A large-scale dataset of multi-view images

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:17.113463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4a259286-48f1-47d0-a9cf-585956cead79 · outbound

This paper cites Text2nerf: Text-driven 3d scene generation with neu- ral radiance fields.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Text2nerf: Text-driven 3d scene generation with neu- ral radiance fields

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:16.242966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 591eeed9-42a9-4ae3-be31-800ee85d717e · outbound

This paper cites Stereo Magnification: Learning View Synthesis using Multiplane Images.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Stereo Magnification: Learning View Synthesis using Multiplane Images

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:16.343562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3a94d99-51b1-46b3-99db-9f317e9d503f · outbound

This paper cites Fsgs: Real-time few-shot view synthesis using gaussian splatting.

Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards Fsgs: Real-time few-shot view synthesis using gaussian splatting

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:16.798793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers