mlsanityData to 14 Oct 2026

Birth and Death of a Rose

arXiv 2412.05278 ↗First posted 6 Dec 2024cs.CV cs.GRcited by 7

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Abstract (arXiv)

We study the problem of generating temporal object intrinsics -- temporally evolving sequences of object geometry, reflectance, and texture, such as a blooming rose -- from pre-trained 2D foundation models. Unlike conventional 3D modeling and animation techniques that require extensive manual effort and expertise, we introduce a method that generates such assets with signals distilled from pre-trained 2D diffusion models. To ensure the temporal consistency of object intrinsics, we propose Neural Templates for temporal-state-guided distillation, derived automatically from image features from self-supervised learning. Our method can generate high-quality temporal object intrinsics for several natural phenomena and enable the sampling and controllable rendering of these dynamic objects from any viewpoint, under any environmental lighting conditions, at any time of their lifespan. Project website: https://chen-geng.com/rose4d

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 63 of its 82 references that are in the map. First posted on arXiv 6 Dec 2024.

Builds on

63 of 82 references.

References · 63

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  5. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,968
  6. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  7. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  8. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  9. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
  10. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  11. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,581
  12. 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,261
38 more
  1. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,245
  2. 2023Consistency Modelscited by 1,822
  3. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,712
  4. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,489
  5. 2023Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inferencecited by 846
  6. 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 746
  7. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 687
  8. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  9. 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
  10. 2021Action-Conditioned 3D Human Motion Synthesis with Transformer VAEcited by 501
  11. 2020NeRD: Neural Reflectance Decomposition from Image Collectionscited by 449
  12. 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 335
  13. 2022NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstructioncited by 314
  14. 2023TEXTure: Text-Guided Texturing of 3D Shapescited by 304
  15. 2023ImageDream: Image-Prompt Multi-view Diffusion for 3D Generationcited by 257
  16. 2022Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Renderingcited by 217
  17. 2021BANMo: Building Animatable 3D Neural Models from Many Casual Videoscited by 197
  18. 2023DreamGaussian4D: Generative 4D Gaussian Splattingcited by 194
  19. 20234D-fy: Text-to-4D Generation Using Hybrid Score Distillation Samplingcited by 185
  20. 2023MotionDirector: Motion Customization of Text-to-Video Diffusion Modelscited by 173
  21. 2023Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Modelscited by 169
  22. 2023TensoIR: Tensorial Inverse Renderingcited by 168
  23. 2024L4GM: Large 4D Gaussian Reconstruction Modelcited by 144
  24. 2024SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistencycited by 144
  25. 2023Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyondcited by 139
  26. 2023Consistent4D: Consistent 360deg Dynamic Object Generation from Monocular Videocited by 125
  27. 2022MagicPony: Learning Articulated 3D Animals in the Wildcited by 112
  28. 2024STAG4D: Spatial-Temporal Anchored Generative 4D Gaussianscited by 102
  29. 2024GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creationcited by 100
  30. 2024Diffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Modelscited by 100
  31. 2024DiLightNet: Fine-grained Lighting Control for Diffusion-based Image Generationcited by 93
  32. 2024Neural Gaffer: Relighting Any Object via Diffusioncited by 91
  33. 2023VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimationcited by 82
  34. 2022LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discoverycited by 66
  35. 20244Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Modelscited by 64
  36. 2021DOVE: Learning Deformable 3D Objects by Watching Videoscited by 61
  37. 2024Learning the 3D Fauna of the Webcited by 59
  38. 2024DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representationcited by 58

50 most cited of 63 All 63 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 5.

7 papers.

  1. 2025SV4D 2.0: Enhancing Spatio-Temporal Consistency in Multi-View Video Diffusion for High-Quality 4D Generationcited by 48
  2. 2026PerpetualWonder: Long-Horizon Action-Conditioned 4D Scene Generationcited by 9
  3. 2025Textured 3D Regenerative Morphing with 3D Diffusion Priorcited by 6
  4. 2026Choreographing a World of Dynamic Objectscited by 5
  5. 2026Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fieldscited by 2
  6. 2026Visual General Intelligence: A White Papercited by 1
  7. 2026HAT-4D: Lifting Monocular Video for 4D Multi-Object Interactions via Human-Agent Collaborationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Breathing New Life into 3D Assets with Generative Repainting
  2. 20253D Object Manipulation in a Single Image using Generative Models
  3. 2024Bringing Objects to Life: training-free 4D generation from 3D objects through view consistent noise
  4. 2024IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illumination
  5. 2023Learning a Diffusion Prior for NeRFs
  6. 2025PractiLight: Practical Light Control Using Foundational Diffusion Models
  7. 2024GenLit: Reformulating Single-Image Relighting as Video Generation
  8. 2023Generative Image Dynamics