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Recent progress in video generation has led to substantial improvements in visual fidelity, yet ensuring physically consistent motion remains a fundamental challenge. Intuitively, this limitation can be attributed to the fact that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Cong Wang , Hanxin Zhu , Xiao Tang , Jiayi Luo , Xin Jin , Long Chen , Zhibo Chen

Synthesizing physics-grounded 3D assets is a critical bottleneck for interactive virtual worlds and embodied AI. Existing methods predominantly focus on static geometry, overlooking the functional properties essential for interaction. We…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Yunhan Yang , Chunshi Wang , Junliang Ye , Yang Li , Zanxin Chen , Zehuan Huang , Yao Mu , Zhuo Chen , Chunchao Guo , Xihui Liu

Recent advances in generative video modeling, driven by large-scale datasets and powerful architectures, have yielded remarkable visual realism. However, emerging evidence suggests that simply scaling data and model size does not endow…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Ying Shen , Jerry Xiong , Tianjiao Yu , Ismini Lourentzou

Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images from text, due to the much larger dataset and higher…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Taegyeong Lee , Soyeong Kwon , Taehwan Kim

The field of photorealistic 3D avatar reconstruction and generation has garnered significant attention in recent years; however, animating such avatars remains challenging. Recent advances in diffusion models have notably enhanced the…

With recent developments in Embodied Artificial Intelligence (EAI) research, there has been a growing demand for high-quality, large-scale interactive scene generation. While prior methods in scene synthesis have prioritized the naturalness…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yandan Yang , Baoxiong Jia , Peiyuan Zhi , Siyuan Huang

Talking head synthesis is a promising approach for the video production industry. Recently, a lot of effort has been devoted in this research area to improve the generation quality or enhance the model generalization. However, there are few…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Shuai Shen , Wenliang Zhao , Zibin Meng , Wanhua Li , Zheng Zhu , Jie Zhou , Jiwen Lu

Diffusion models can generate realistic videos, but existing methods rely on implicitly learning physical reasoning from large-scale text-video datasets, which is costly, difficult to scale, and still prone to producing implausible motions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Yutong Hao , Chen Chen , Ajmal Saeed Mian , Chang Xu , Daochang Liu

Video inpainting is the task of filling a region in a video in a visually convincing manner. It is very challenging due to the high dimensionality of the data and the temporal consistency required for obtaining convincing results. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Nicolas Cherel , Andrés Almansa , Yann Gousseau , Alasdair Newson

Video-conditioned 4D shape generation aims to recover time-varying 3D geometry and view-consistent appearance directly from an input video. In this work, we introduce a native video-to-4D shape generation framework that synthesizes a single…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Jiraphon Yenphraphai , Ashkan Mirzaei , Jianqi Chen , Jiaxu Zou , Sergey Tulyakov , Raymond A. Yeh , Peter Wonka , Chaoyang Wang

Recent advancements in 2D and 3D generative models have expanded the capabilities of computer vision. However, generating high-quality 4D dynamic content from a single static image remains a significant challenge. Traditional methods have…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jing Yang , Yufeng Yang

We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100$\times$ faster than previous works while possessing superior rendering quality. Our approach shifts from the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinyang Li , Tengfei Wang , Zixiao Gu , Shengchuan Zhang , Chunchao Guo , Liujuan Cao

We introduce Control4D, an innovative framework for editing dynamic 4D portraits using text instructions. Our method addresses the prevalent challenges in 4D editing, notably the inefficiencies of existing 4D representations and the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Ruizhi Shao , Jingxiang Sun , Cheng Peng , Zerong Zheng , Boyao Zhou , Hongwen Zhang , Yebin Liu

Images as an artistic medium often rely on specific camera angles and lens distortions to convey ideas or emotions; however, such precise control is missing in current text-to-image models. We propose an efficient and general solution that…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Edurne Bernal-Berdun , Ana Serrano , Belen Masia , Matheus Gadelha , Yannick Hold-Geoffroy , Xin Sun , Diego Gutierrez

Creative image generation has emerged as a compelling area of research, driven by the need to produce novel and high-quality images that expand the boundaries of imagination. In this work, we propose a novel framework for creative…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Kunpeng Song , Ahmed Elgammal

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

While modern diffusion models excel at generating diverse single images, extending this to sequential generation reveals a fundamental challenge: balancing narrative dynamism with multi-character coherence. Existing methods often falter at…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Qi Zhao , Jun Chen , Ivor Tsang , Guang Dai

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data and constrained computation resources, hampering their ability to generate high-fidelity…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Haonan Qiu , Shiwei Zhang , Yujie Wei , Ruihang Chu , Hangjie Yuan , Xiang Wang , Yingya Zhang , Ziwei Liu

We present 4DiM, a cascaded diffusion model for 4D novel view synthesis (NVS), supporting generation with arbitrary camera trajectories and timestamps, in natural scenes, conditioned on one or more images. With a novel architecture and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Daniel Watson , Saurabh Saxena , Lala Li , Andrea Tagliasacchi , David J. Fleet