Any-to-3D Generation via Hybrid Diffusion Supervision | Paper Citation Record

Observation 58a48177-60ee-4fdc-a9b5-725dc1b10bd4 · outbound

This paper cites A Comprehensive Survey on 3D Content Generation.

Any-to-3D Generation via Hybrid Diffusion Supervision A Comprehensive Survey on 3D Content Generation

Reference 1

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Observation ab03ce1c-0c6e-4f5b-9e17-ecf0049af528 · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision MVDream: Multi-view Diffusion for 3D Generation

Reference 2

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Observation 53913581-a70d-492d-ba92-411094513296 · outbound

This paper cites DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior.

Any-to-3D Generation via Hybrid Diffusion Supervision DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior

Reference 3

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Observation 12200ea4-2b8b-4f1c-a655-ef1cb38aeb84 · outbound

This paper cites CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model.

Any-to-3D Generation via Hybrid Diffusion Supervision CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model

Reference 4

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Observation 17bbf6d2-9bdd-4f05-a353-e177767ba10c · outbound

This paper cites Scalable diffusion models with transformers,.

Any-to-3D Generation via Hybrid Diffusion Supervision Scalable diffusion models with transformers,

Reference 5

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Observation 61fc271f-8f2d-437c-b16b-4651d3bb08b3 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Any-to-3D Generation via Hybrid Diffusion Supervision U-net: Convolutional networks for biomedical image segmentation,

Reference 6

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Observation 620e5ff1-740d-4c29-9519-64e408ceb3cd · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Any-to-3D Generation via Hybrid Diffusion Supervision Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 7

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Observation f76566cb-5053-4abd-a366-4928b4792962 · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision High- resolution image synthesis with latent diffusion models,

Reference 8

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Observation f97915fa-8ab2-4c8c-9415-1a6793b0dd37 · outbound

This paper cites Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation,

Reference 9

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Observation 4b764b39-6668-41aa-8e23-6dc37b695d8c · outbound

This paper cites Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation,

Reference 10

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Observation b4f8d8df-8334-450c-98b3-f36758c75bda · outbound

This paper cites Consistent3d: Towards consistent high-fidelity text-to-3d generation with deterministic sampling prior,.

Any-to-3D Generation via Hybrid Diffusion Supervision Consistent3d: Towards consistent high-fidelity text-to-3d generation with deterministic sampling prior,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:10.156598Z

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Observation 0795ee22-0282-4593-956c-5be708aa389c · outbound

This paper cites Score distillation sampling with learned manifold corrective,.

Any-to-3D Generation via Hybrid Diffusion Supervision Score distillation sampling with learned manifold corrective,

Reference 12

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Observation ccef9134-5c18-47b1-a5ba-466e9707076e · outbound

This paper cites Taming Mode Collapse in Score Distillation for Text-to-3D Generation.

Any-to-3D Generation via Hybrid Diffusion Supervision Taming Mode Collapse in Score Distillation for Text-to-3D Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.927827Z

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Observation 69cf0a3c-c85f-4c2a-aff1-6f56c6d6075b · outbound

This paper cites Prolific- dreamer: High-fidelity and diverse text-to-3d generation with variational score distillation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Prolific- dreamer: High-fidelity and diverse text-to-3d generation with variational score distillation,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.932799Z

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Observation f8e4a336-e408-42c7-81ad-1da07bd3d4e9 · outbound

This paper cites Text2mesh: Text-driven neural stylization for meshes,.

Any-to-3D Generation via Hybrid Diffusion Supervision Text2mesh: Text-driven neural stylization for meshes,

Reference 15

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Observation 325a509d-8d1c-4246-9f42-31754ffbae7b · outbound

This paper cites Cad: Photorealistic 3d generation via adversarial dis- tillation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Cad: Photorealistic 3d generation via adversarial dis- tillation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:10.112681Z

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Observation 25272064-4dff-4f97-8c82-69108bc4d387 · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.946191Z

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Observation c7f2fbb1-06e5-4912-8725-19b4e7dafbb6 · outbound

This paper cites Make-it-3d: High-fidelity 3d creation from a single image with diffu- sion prior,.

Any-to-3D Generation via Hybrid Diffusion Supervision Make-it-3d: High-fidelity 3d creation from a single image with diffu- sion prior,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.950956Z

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Observation b2bb9bbb-7f2b-4f0e-b993-bdd9af1513a1 · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision Realfusion: 360deg reconstruction of any object from a single image,

Reference 19

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Observation 5fdb51db-88ad-4a3e-bb6e-2ea921db3796 · outbound

This paper cites Imagebind: One embedding space to bind them all,.

Any-to-3D Generation via Hybrid Diffusion Supervision Imagebind: One embedding space to bind them all,

Reference 20

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Observation e3e7c479-c0d2-4dae-8828-aafe5bf81840 · outbound

This paper cites Any-to-any generation via composable diffusion,.

Any-to-3D Generation via Hybrid Diffusion Supervision Any-to-any generation via composable diffusion,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:10.067350Z

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Observation c8402f07-2dc1-4427-b397-75901738a4e1 · outbound

This paper cites Dreamfusion: Text- to-3d using 2d diffusion,.

Any-to-3D Generation via Hybrid Diffusion Supervision Dreamfusion: Text- to-3d using 2d diffusion,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:10.051830Z

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Observation f1a2d67b-b25a-4a63-90e5-9a02c3543115 · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision Zero-1-to-3: Zero-shot one image to 3d object,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.973776Z

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Observation 8dad3f68-d79e-478a-9369-ab314585df38 · outbound

This paper cites Mip-nerf: A multiscale representation for anti- aliasing neural radiance fields,.

Any-to-3D Generation via Hybrid Diffusion Supervision Mip-nerf: A multiscale representation for anti- aliasing neural radiance fields,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.978522Z

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Observation 1ea507c1-f81b-471a-962c-4a8e3753c7ef · outbound

This paper cites Instant neural graphics primitives with a multiresolution hash encoding,.

Any-to-3D Generation via Hybrid Diffusion Supervision Instant neural graphics primitives with a multiresolution hash encoding,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.982694Z

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Observation 8edee7e6-22fa-4a4a-b252-dad2923d0e82 · outbound

This paper cites Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthe- sis,.

Any-to-3D Generation via Hybrid Diffusion Supervision Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthe- sis,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:10.005037Z

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Observation f7b5b759-ce9c-40ce-a036-366ed4553002 · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications,.

Any-to-3D Generation via Hybrid Diffusion Supervision Diffusion models: A comprehensive survey of methods and applications,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.991441Z

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Observation 26f0b8c1-cdb7-4c16-8e8d-f4470e745cb3 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Any-to-3D Generation via Hybrid Diffusion Supervision Score-Based Generative Modeling through Stochastic Differential Equations

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:08.995743Z

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Observation d15f644d-4a79-416d-8021-b2b826610ef0 · outbound

This paper cites Denoising diffusion probabilistic models,.

Any-to-3D Generation via Hybrid Diffusion Supervision Denoising diffusion probabilistic models,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.000129Z

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Observation c1627c15-bda4-46ff-af79-dc587a4ce8b7 · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision Learning transferable visual models from natural language supervision,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.004704Z

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Observation c752e858-f635-414a-8e67-cda7edfef26b · outbound

This paper cites Vector quantized diffusion model for text-to-image synthesis,.

Any-to-3D Generation via Hybrid Diffusion Supervision Vector quantized diffusion model for text-to-image synthesis,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.959853Z

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Observation 7ea2d145-5880-468b-87c6-958f42bd2fde · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Any-to-3D Generation via Hybrid Diffusion Supervision Diffusion models beat gans on image synthesis,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.013153Z

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Observation b60c36b8-a853-4783-861a-7a0944dabc67 · outbound

This paper cites Improving diffusion-based image synthesis with context pre- diction,.

Any-to-3D Generation via Hybrid Diffusion Supervision Improving diffusion-based image synthesis with context pre- diction,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.933664Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a0d02342-8316-442f-8a2d-ba0a69d5d526 · outbound

This paper cites Shifted diffusion for text-to-image generation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Shifted diffusion for text-to-image generation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.918543Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 91f627df-ae0e-4541-a448-a3415e41534e · outbound

This paper cites Text2video-zero: Text-to-image diffusion models are zero-shot video generators,.

Any-to-3D Generation via Hybrid Diffusion Supervision Text2video-zero: Text-to-image diffusion models are zero-shot video generators,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.027051Z

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Observation 76e529bc-9e94-47fe-9c0b-8ded0e7a27de · outbound

This paper cites Videofusion: Decomposed diffusion models for high-quality video generation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Videofusion: Decomposed diffusion models for high-quality video generation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.893071Z

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Observation f62fb30d-c7dc-42a7-be9b-2f2feddca30b · outbound

This paper cites Vidm: Video implicit diffusion models,.

Any-to-3D Generation via Hybrid Diffusion Supervision Vidm: Video implicit diffusion models,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.037210Z

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Observation 402b17df-3908-41c7-a353-1bbe49809c2c · outbound

This paper cites LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models.

Any-to-3D Generation via Hybrid Diffusion Supervision LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.041883Z

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Observation cbc742d2-1eef-4fd2-b7d4-148dec3d0f0a · outbound

This paper cites Prodiff: Progressive fast diffusion model for high-quality text-to-speech,.

Any-to-3D Generation via Hybrid Diffusion Supervision Prodiff: Progressive fast diffusion model for high-quality text-to-speech,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.867485Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f53e03e5-aef3-4931-98b6-8cb45fd5232d · outbound

This paper cites Taming diffusion models for audio-driven co-speech gesture generation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Taming diffusion models for audio-driven co-speech gesture generation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.851715Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1c8bda65-74c7-4d6c-b79e-174173688c26 · outbound

This paper cites Speech enhancement and dereverberation with diffusion-based genera- tive models,.

Any-to-3D Generation via Hybrid Diffusion Supervision Speech enhancement and dereverberation with diffusion-based genera- tive models,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.055185Z

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Observation c1009c3e-ef11-4e4d-a58d-d449c68cef03 · outbound

This paper cites Storm: A diffusion-based stochastic regeneration model for speech enhancement and dereverberation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Storm: A diffusion-based stochastic regeneration model for speech enhancement and dereverberation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.826556Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ffa2b3a8-f75f-4826-80b1-5a5436ff3713 · outbound

This paper cites HyperFields: Towards Zero-Shot Generation of NeRFs from Text.

Any-to-3D Generation via Hybrid Diffusion Supervision HyperFields: Towards Zero-Shot Generation of NeRFs from Text

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:06:09.369297Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4046219f-73da-4020-8c5c-9b4648149132 · outbound

This paper cites Texfusion: Synthesiz- ing 3d textures with text-guided image diffusion models,.

Any-to-3D Generation via Hybrid Diffusion Supervision Texfusion: Synthesiz- ing 3d textures with text-guided image diffusion models,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.810996Z

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Observation 96ec87b7-777f-414e-8707-6f16341013e7 · outbound

This paper cites Luciddreamer: Towards high-fidelity text-to-3d generation via interval score matching,.

Any-to-3D Generation via Hybrid Diffusion Supervision Luciddreamer: Towards high-fidelity text-to-3d generation via interval score matching,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.072978Z

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Observation c969aad8-aa71-4917-aaf1-439b7ece00dc · outbound

This paper cites Scenetex: High-quality texture synthesis for indoor scenes via diffusion priors,.

Any-to-3D Generation via Hybrid Diffusion Supervision Scenetex: High-quality texture synthesis for indoor scenes via diffusion priors,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.785723Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 152a28b7-d752-4fc1-9678-ea58cfdeb0b9 · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision High- resolution image synthesis with latent diffusion models,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.081939Z

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Observation 9c6ebb7f-ce0b-4c56-aee1-5138a6bc3ecd · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision SyncDreamer: Generating Multiview-consistent Images from a Single-view Image

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.086742Z

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Observation a1758340-b61d-41f2-8a1f-7a3ab483c63f · outbound

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

Any-to-3D Generation via Hybrid Diffusion Supervision Objaverse: A universe of annotated 3d objects,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.760556Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 326f62a7-0b69-4885-9f52-31750f438126 · outbound

This paper cites Objaverse-xl: A uni- verse of 10m+ 3d objects,.

Any-to-3D Generation via Hybrid Diffusion Supervision Objaverse-xl: A uni- verse of 10m+ 3d objects,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.745915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c960da25-e218-4a06-b48b-62718270d6cc · outbound

This paper cites Omnivore: A single model for many visual modalities,.

Any-to-3D Generation via Hybrid Diffusion Supervision Omnivore: A single model for many visual modalities,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.100545Z

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Observation 2ca5aaf4-4b5a-41ac-b0b2-5f6cc8611c7c · outbound

This paper cites PolyViT: Co-training Vision Transformers on Images, Videos and Audio.

Any-to-3D Generation via Hybrid Diffusion Supervision PolyViT: Co-training Vision Transformers on Images, Videos and Audio

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.105043Z

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Observation d455fe45-28c2-4493-80df-62d3e04ce503 · outbound

This paper cites Look, listen and learn,.

Any-to-3D Generation via Hybrid Diffusion Supervision Look, listen and learn,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.721471Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 66dd7062-c45f-4416-992a-93c83159a1cc · outbound

This paper cites Omnimae: Single model masked pretraining on images and videos,.

Any-to-3D Generation via Hybrid Diffusion Supervision Omnimae: Single model masked pretraining on images and videos,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.707135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c2ff91f4-95fa-48f7-83a4-1192399cb610 · outbound

This paper cites Audio-visual instance discrimination with cross-modal agreement,.

Any-to-3D Generation via Hybrid Diffusion Supervision Audio-visual instance discrimination with cross-modal agreement,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.692449Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f68eb4b9-c82a-4258-a31b-a1e0edbbc09b · outbound

This paper cites Contrastive multiview coding,.

Any-to-3D Generation via Hybrid Diffusion Supervision Contrastive multiview coding,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.122829Z

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Unavailable: canonical work link unavailable.

Observation 9597dfb0-6242-4426-af2a-9c4b64904947 · outbound

This paper cites Bevt: Bert pretraining of video transformers,.

Any-to-3D Generation via Hybrid Diffusion Supervision Bevt: Bert pretraining of video transformers,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.667448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f8a5fd88-b8d2-4d96-b629-78a21a56a2e9 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Any-to-3D Generation via Hybrid Diffusion Supervision An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.131536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccd53418-b010-4471-988f-95f55e04344f · outbound

This paper cites Flamingo: a visual language model for few-shot learning,.

Any-to-3D Generation via Hybrid Diffusion Supervision Flamingo: a visual language model for few-shot learning,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.136242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e313d8b7-e60b-4394-84aa-ce78ae8bd06c · outbound

This paper cites Unifying vision-and-language tasks via text generation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Unifying vision-and-language tasks via text generation,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.140586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbc33707-dc53-4f18-9fd3-00853989f456 · outbound

This paper cites Merlot: Multimodal neural script knowledge models,.

Any-to-3D Generation via Hybrid Diffusion Supervision Merlot: Multimodal neural script knowledge models,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.630843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7a20f2a2-126e-4a0b-b512-feebae9509d2 · outbound

This paper cites Multimodal few-shot learning with frozen language models,.

Any-to-3D Generation via Hybrid Diffusion Supervision Multimodal few-shot learning with frozen language models,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.613813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d1262267-e2dc-430e-81d1-5e465e451c67 · outbound

This paper cites Enhancing Visual Grounding and Generalization: A Multi-Task Cycle Training Approach for Vision-Language Models.

Any-to-3D Generation via Hybrid Diffusion Supervision Enhancing Visual Grounding and Generalization: A Multi-Task Cycle Training Approach for Vision-Language Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.154447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91929523-abef-4ee5-bd5f-f24e179c6f8b · outbound

This paper cites Tvlt: Textless vision- language transformer,.

Any-to-3D Generation via Hybrid Diffusion Supervision Tvlt: Textless vision- language transformer,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.598574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 24568667-8c93-4b8e-ae8e-e39e705dc7ad · outbound

This paper cites i-code: An integrative and composable multimodal learning framework,.

Any-to-3D Generation via Hybrid Diffusion Supervision i-code: An integrative and composable multimodal learning framework,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.583209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bed8ef28-4106-4293-8a4c-2788d6ce3475 · outbound

This paper cites Merlot reserve: Neural script knowledge through vision and language and sound,.

Any-to-3D Generation via Hybrid Diffusion Supervision Merlot reserve: Neural script knowledge through vision and language and sound,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.566661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 278ba3f8-a417-4148-ba47-941a6f9cfa78 · outbound

This paper cites Codi-2: In-context interleaved and interactive any-to-any generation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Codi-2: In-context interleaved and interactive any-to-any generation,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.551448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0d7bda40-a9b7-4578-9fab-bd0def96b275 · outbound

This paper cites Clap learning audio concepts from natural language supervision,.

Any-to-3D Generation via Hybrid Diffusion Supervision Clap learning audio concepts from natural language supervision,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.178506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14becb8c-e340-404d-b335-eae95a2b7a86 · outbound

This paper cites AudioLDM: Text-to-Audio Generation with Latent Diffusion Models.

Any-to-3D Generation via Hybrid Diffusion Supervision AudioLDM: Text-to-Audio Generation with Latent Diffusion Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.182850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 165f4ef6-ebb0-441c-b50c-e4cf30ccecd4 · outbound

This paper cites ClipCap: CLIP Prefix for Image Captioning.

Any-to-3D Generation via Hybrid Diffusion Supervision ClipCap: CLIP Prefix for Image Captioning

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.187306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffde865b-5216-4021-805b-079c3d710f1d · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Any-to-3D Generation via Hybrid Diffusion Supervision Representation Learning with Contrastive Predictive Coding

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.192123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32346f7b-7d32-4e2c-bbde-806ea81e4236 · outbound

This paper cites HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance.

Any-to-3D Generation via Hybrid Diffusion Supervision HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.196597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93f1e07f-3939-4189-b9d5-5a20c346064f · outbound

This paper cites Magic3d: High-resolution text-to- 3d content creation,.

Any-to-3D Generation via Hybrid Diffusion Supervision Magic3d: High-resolution text-to- 3d content creation,

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T15:06:09.201401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6c33e85-a032-46af-9e58-f116ec26e3f9 · outbound

This paper cites threestudio: A unified framework for 3d content generation,.

Any-to-3D Generation via Hybrid Diffusion Supervision threestudio: A unified framework for 3d content generation,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:06:09.518344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Reference resolution

Outbound references

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