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Existing methods for human motion control in video generation typically rely on either 2D poses or explicit 3D parametric models (e.g., SMPL) as control signals. However, 2D poses rigidly bind motion to the driving viewpoint, precluding…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Zhixue Fang , Xu He , Songlin Tang , Haoxian Zhang , Qingfeng Li , Xiaoqiang Liu , Pengfei Wan , Kun Gai

3D structure modeling is essential across scales, enabling applications from fluid simulation and 3D reconstruction to protein folding and molecular docking. Yet, despite shared 3D spatial patterns, current approaches remain fragmented,…

Machine Learning · Computer Science 2025-10-10 Shuqi Lu , Haowei Lin , Lin Yao , Zhifeng Gao , Xiaohong Ji , Yitao Liang , Weinan E , Linfeng Zhang , Guolin Ke

We introduce Uni4D, a unified framework for large scale open vocabulary 3D retrieval and controlled 4D generation based on structured three level alignment across text, 3D models, and image modalities. Built upon the Align3D 130 dataset,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Philip Xu

Video generation technologies are developing rapidly and have broad potential applications. Among these technologies, camera control is crucial for generating professional-quality videos that accurately meet user expectations. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Wanquan Feng , Jiawei Liu , Pengqi Tu , Tianhao Qi , Mingzhen Sun , Tianxiang Ma , Songtao Zhao , Siyu Zhou , Qian He

Video is a rich and scalable source of 3D/4D visual observations, and camera control is a key capability for video generation models to produce geometrically meaningful content. Existing approaches typically learn a mapping from camera…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Chen Hou , Christian Rupprecht

Reconstructing and semantically interpreting 3D scenes from sparse 2D views remains a fundamental challenge in computer vision. Conventional methods often decouple semantic understanding from reconstruction or necessitate costly per-scene…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Xiangyu Sun , Haoyi Jiang , Liu Liu , Seungtae Nam , Gyeongjin Kang , Xinjie Wang , Wei Sui , Zhizhong Su , Wenyu Liu , Xinggang Wang , Eunbyung Park

Monocular dynamic video reconstruction faces significant challenges in dynamic human scenes due to geometric inconsistencies and resolution degradation issues. Existing methods lack 3D human structural understanding, producing geometrically…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Weitao Xiong , Zhiyuan Yuan , Jiahao Lu , Chengfeng Zhao , Peng Li , Yuan Liu

Performing 3D dense captioning and visual grounding requires a common and shared understanding of the underlying multimodal relationships. However, despite some previous attempts on connecting these two related tasks with highly…

Computer Vision and Pattern Recognition · Computer Science 2022-12-05 Dave Zhenyu Chen , Ronghang Hu , Xinlei Chen , Matthias Nießner , Angel X. Chang

Cinematic storytelling is profoundly shaped by the artful manipulation of photographic elements such as depth of field and exposure. These effects are crucial in conveying mood and creating aesthetic appeal. However, controlling these…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Huiqiang Sun , Liao Shen , Zhan Peng , Kun Wang , Size Wu , Yuhang Zang , Tianqi Liu , Zihao Huang , Xingyu Zeng , Zhiguo Cao , Wei Li , Chen Change Loy

In this work, we present an effective multi-view approach to closed-loop end-to-end learning of precise manipulation tasks that are 3D in nature. Our method learns to accomplish these tasks using multiple statically placed but uncalibrated…

Robotics · Computer Science 2021-04-02 Iretiayo Akinola , Jacob Varley , Dmitry Kalashnikov

We present Human3R, a unified, feed-forward framework for online 4D human-scene reconstruction, in the world frame, from casually captured monocular videos. Unlike previous approaches that rely on multi-stage pipelines, iterative…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Yue Chen , Xingyu Chen , Yuxuan Xue , Anpei Chen , Yuliang Xiu , Gerard Pons-Moll

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control over four key video elements: foreground subject, background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Jingyun Liang , Jingkai Zhou , Shikai Li , Chenjie Cao , Lei Sun , Yichen Qian , Weihua Chen , Fan Wang

Recent advances in 3D vision have led to specialized models for either 3D understanding (e.g., shape classification, segmentation, reconstruction) or 3D generation (e.g., synthesis, completion, and editing). However, these tasks are often…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Peng Huang , Yifeng Chen , Zeyu Zhang , Hao Tang

Video fundamentally intertwines two crucial axes: the dynamic content of a scene and the camera motion through which it is observed. However, existing generation models often entangle these factors, limiting independent control. In this…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Yukun Wang , Ruihuang Li , Jiale Tao , Shiyuan Yang , Liyi Chen , Zhantao Yang , Handz , Yulan Guo , Shuai Shao , Qinglin Lu

Data-efficient training of robust robot policies is the key to unlocking automation in a wide array of novel tasks. Current systems require large volumes of demonstrations to achieve robustness, which is impractical in many applications.…

Robotics · Computer Science 2026-03-10 Adam Hung , Bardienus Pieter Duisterhof , Jeffrey Ichnowski

Building a robust perception module is crucial for visuomotor policy learning. While recent methods incorporate pre-trained 2D foundation models into robotic perception modules to leverage their strong semantic understanding, they struggle…

Robotics · Computer Science 2025-07-14 Wenbo Cui , Chengyang Zhao , Yuhui Chen , Haoran Li , Zhizheng Zhang , Dongbin Zhao , He Wang

Controllable 3D human avatars have found widespread applications in 3D games, the metaverse, and AR/VR scenarios. The conventional approach to creating such a 3D avatar requires a lengthy, intricate pipeline encompassing appearance…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Jiahe Zhu , Xinyao Wang , Yiyu Zhuang , Yanwen Wang , Jing Tian , Yao Yao , Hao Zhu

Existing point cloud based 3D detectors are designed for the particular scene, either indoor or outdoor ones. Because of the substantial differences in object distribution and point density within point clouds collected from various…

Computer Vision and Pattern Recognition · Computer Science 2023-10-10 Zhenyu Wang , Yali Li , Xi Chen , Hengshuang Zhao , Shengjin Wang

3D human pose estimation from a monocular video has recently seen significant improvements. However, most state-of-the-art methods are kinematics-based, which are prone to physically implausible motions with pronounced artifacts. Current…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Jiefeng Li , Siyuan Bian , Chao Xu , Gang Liu , Gang Yu , Cewu Lu