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Related papers: Tex4D: Zero-shot 4D Scene Texturing with Video Dif…

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In this paper, we present TEXTure, a novel method for text-guided generation, editing, and transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model, TEXTure applies an iterative scheme that paints a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Elad Richardson , Gal Metzer , Yuval Alaluf , Raja Giryes , Daniel Cohen-Or

Significant progress has been made for speech-driven 3D face animation, but most works focus on learning the motion of mesh/geometry, ignoring the impact of dynamic texture. In this work, we reveal that dynamic texture plays a key role in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Xuanchen Li , Jianyu Wang , Yuhao Cheng , Yikun Zeng , Xingyu Ren , Wenhan Zhu , Weiming Zhao , Yichao Yan

Although powerful for image generation, consistent and controllable video is a longstanding problem for diffusion models. Video models require extensive training and computational resources, leading to high costs and large environmental…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Muhammad Haaris Khan , Hadrien Reynaud , Bernhard Kainz

Recent research on texture synthesis for 3D shapes benefits a lot from dramatically developed 2D text-to-image diffusion models, including inpainting-based and optimization-based approaches. However, these methods ignore the modal gap…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Shang Liu , Chaohui Yu , Chenjie Cao , Wen Qian , Fan Wang

Recent advances in diffusion-based generative models have established a new paradigm for image and video relighting. However, extending these capabilities to 4D relighting remains challenging, due primarily to the scarcity of paired 4D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Zhenghuang Wu , Kang Chen , Zeyu Zhang , Hao Tang

We introduce Geo4D, a method to repurpose video diffusion models for monocular 3D reconstruction of dynamic scenes. By leveraging the strong dynamic priors captured by large-scale pre-trained video models, Geo4D can be trained using only…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Zeren Jiang , Chuanxia Zheng , Iro Laina , Diane Larlus , Andrea Vedaldi

Dynamic 3D (4D) content generation, particularly text-to-4D, remains a challenging and under-explored problem due to its inherent spatiotemporal complexity. Existing text-to-4D methods typically avoid direct mesh generation due to inherent…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Sisi Dai , Xinxin Su , Ruizhen Hu , Kai Xu

We present TexMesh, a novel approach to reconstruct detailed human meshes with high-resolution full-body texture from RGB-D video. TexMesh enables high quality free-viewpoint rendering of humans. Given the RGB frames, the captured…

Computer Vision and Pattern Recognition · Computer Science 2020-09-22 Tiancheng Zhi , Christoph Lassner , Tony Tung , Carsten Stoll , Srinivasa G. Narasimhan , Minh Vo

Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Shuai Yang , Yifan Zhou , Ziwei Liu , Chen Change Loy

This paper presents TexRO, a novel method for generating delicate textures of a known 3D mesh by optimizing its UV texture. The key contributions are two-fold. We propose an optimal viewpoint selection strategy, that finds the most…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinbo Wu , Xing Liu , Chenming Wu , Xiaobo Gao , Jialun Liu , Xinqi Liu , Chen Zhao , Haocheng Feng , Errui Ding , Jingdong Wang

Current video-to-4D methods struggle with complex topology changes, transparent materials, thin structures, and inner surfaces. We present Helix4D, a dynamic mesh generation framework by inheriting the expressive representation of Trellis2,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Jiraphon Yenphraphai , Jianqi Chen , Jian Wang , Gordon Qian , Sergey Tulyakov , Rameen Abdal , Raymond A. Yeh , Peter Wonka , Chaoyang Wang

Numerous methods have been proposed for probabilistic generative modelling of 3D objects. However, none of these is able to produce textured objects, which renders them of limited use for practical tasks. In this work, we present the first…

Computer Vision and Pattern Recognition · Computer Science 2020-04-10 Paul Henderson , Vagia Tsiminaki , Christoph H. Lampert

We present V2M4, a novel 4D reconstruction method that directly generates a usable 4D mesh animation asset from a single monocular video. Unlike existing approaches that rely on priors from multi-view image and video generation models, our…

Graphics · Computer Science 2025-07-30 Jianqi Chen , Biao Zhang , Xiangjun Tang , Peter Wonka

Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Existing methods are typically limited to monocular videos,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Tingxi Chen , Ke Hao , Yabo Chen , Zhengxue Cheng , Rong Xie , Li Song , Haibin Huang , Chi Zhang , Xuelong Li

Reconstructing dense geometry for dynamic scenes from a monocular video is a critical yet challenging task. Recent memory-based methods enable efficient online reconstruction, but they fundamentally suffer from a Memory Demand Dilemma: The…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Xudong Cai , Shuo Wang , Peng Wang , Yongcai Wang , Zhaoxin Fan , Wanting Li , Tianbao Zhang , Jianrong Tao , Yeying Jin , Deying Li

This paper introduces a novel approach to synthesize texture to dress up a given 3D object, given a text prompt. Based on the pretrained text-to-image (T2I) diffusion model, existing methods usually employ a project-and-inpaint approach, in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Yuxin Liu , Minshan Xie , Hanyuan Liu , Tien-Tsin Wong

In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation fidelity and strong generalizability. Previous methods based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Kailu Wu , Fangfu Liu , Zhihan Cai , Runjie Yan , Hanyang Wang , Yating Hu , Yueqi Duan , Kaisheng Ma

Recent progress in 4D representations, such as Dynamic NeRF and 4D Gaussian Splatting (4DGS), has enabled dynamic 4D scene reconstruction. However, text-driven 4D scene editing remains under-explored due to the challenge of ensuring both…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Dong In Lee , Hyungjun Doh , Seunggeun Chi , Runlin Duan , Sangpil Kim , Karthik Ramani

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

We propose Mesh4D, a feed-forward model for monocular 4D mesh reconstruction. Given a monocular video of a dynamic object, our model reconstructs the object's complete 3D shape and motion, represented as a deformation field. Our key…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Zeren Jiang , Chuanxia Zheng , Iro Laina , Diane Larlus , Andrea Vedaldi