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Human motion synthesis is an important problem with applications in graphics, gaming and simulation environments for robotics. Existing methods require accurate motion capture data for training, which is costly to obtain. Instead, we…

Computer Vision and Pattern Recognition · Computer Science 2022-08-15 Kevin Xie , Tingwu Wang , Umar Iqbal , Yunrong Guo , Sanja Fidler , Florian Shkurti

The video generation field has witnessed rapid improvements with the introduction of recent diffusion models. While these models have successfully enhanced appearance quality, they still face challenges in generating coherent and natural…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Yaosi Hu , Zhenzhong Chen , Chong Luo

The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-guided 3D object generation has shown great promise in…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Alexander W. Bergman , Wang Yifan , Gordon Wetzstein

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Junjie Cao , Kaizhou Li , Xinchun Yu , Hongxiang Li , Xiaoping Zhang

Creating dynamic, view-consistent videos of customized subjects is highly sought after for a wide range of emerging applications, including immersive VR/AR, virtual production, and next-generation e-commerce. However, despite rapid progress…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Hyun-kyu Ko , Jihyeon Park , Younghyun Kim , Dongheok Park , Eunbyung Park

In recent years, 3D vision has become a crucial field within computer vision, powering a wide range of applications such as autonomous driving, robotics, augmented reality, and medical imaging. This field relies on accurate perception,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Zhen Wang , Dongyuan Li , Yaozu Wu , Tianyu He , Jiang Bian , Renhe Jiang

Text-driven Image to Video Generation (TI2V) aims to generate controllable video given the first frame and corresponding textual description. The primary challenges of this task lie in two parts: (i) how to identify the target objects and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xingrui Wang , Xin Li , Yaosi Hu , Hanxin Zhu , Chen Hou , Cuiling Lan , Zhibo Chen

We present Vista4D, a robust and flexible video reshooting framework that grounds the input video and target cameras in a 4D point cloud. Specifically, given an input video, our method re-synthesizes the scene with the same dynamics from a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Kuan Heng Lin , Zhizheng Liu , Pablo Salamanca , Yash Kant , Ryan Burgert , Yuancheng Xu , Koichi Namekata , Yiwei Zhao , Bolei Zhou , Micah Goldblum , Paul Debevec , Ning Yu

Recent advances in diffusion-based and autoregressive video generation models have achieved remarkable visual realism. However, these models typically lack accurate physical alignment, failing to replicate real-world dynamics in object…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Tao Feng , Xianbing Zhao , Zhenhua Chen , Tien Tsin Wong , Hamid Rezatofighi , Gholamreza Haffari , Lizhen Qu

While 3D hand reconstruction from monocular images has made significant progress, generating accurate and temporally coherent motion estimates from videos remains challenging, particularly during hand-object interactions. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yufei Zhang , Zijun Cui , Jeffrey O. Kephart , Qiang Ji

Inserting 3D objects into videos is a longstanding challenge in computer graphics with applications in augmented reality, virtual try-on, and video composition. Achieving both temporal consistency, or realistic lighting remains difficult,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Chenjian Gao , Lihe Ding , Rui Han , Zhanpeng Huang , Zibin Wang , Tianfan Xue

We present a method for generating physically-based materials for 3D shapes based on a video diffusion transformer architecture. Our method is conditioned on input geometry and a text description, and jointly models multiple material…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Jon Hasselgren , Zheng Zeng , Milos Hasan , Jacob Munkberg

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

Current texture synthesis methods, which generate textures from fixed viewpoints, suffer from inconsistencies due to the lack of global context and geometric understanding. Meanwhile, recent advancements in video generation models have…

Graphics · Computer Science 2025-06-27 Donggoo Kang , Jangyeong Kim , Dasol Jeong , Junyoung Choi , Jeonga Wi , Hyunmin Lee , Joonho Gwon , Joonki Paik

3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints. Existing methods often decompose 3D shapes into a sequence of localized components, treating each element in isolation without…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Ruikai Cui , Weizhe Liu , Weixuan Sun , Senbo Wang , Taizhang Shang , Yang Li , Xibin Song , Han Yan , Zhennan Wu , Shenzhou Chen , Hongdong Li , Pan Ji

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yitong Yang , Xuexin Liu , Yinglin Wang , Jing Wang , Hao Dou , Changshuo Wang , Shuting He

Although recent 3D-native generators have made great progress in synthesizing reliable geometry, they still fall short in achieving realistic appearances. A key obstacle lies in the lack of diverse and high-quality real-world 3D assets with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xinyue Liang , Zhinyuan Ma , Lingchen Sun , Yanjun Guo , Lei Zhang

We present a method to estimate depth of a dynamic scene, containing arbitrary moving objects, from an ordinary video captured with a moving camera. We seek a geometrically and temporally consistent solution to this underconstrained…

Computer Vision and Pattern Recognition · Computer Science 2021-08-04 Zhoutong Zhang , Forrester Cole , Richard Tucker , William T. Freeman , Tali Dekel

Motion-controllable image animation is a fundamental task with a wide range of potential applications. Recent works have made progress in controlling camera or object motion via various motion representations, while they still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yingjie Chen , Yifang Men , Yuan Yao , Miaomiao Cui , Liefeng Bo

Video object segmentation methods like SAM2 achieve strong performance through memory-based architectures but struggle under large viewpoint changes due to reliance on appearance features. Traditional 3D instance segmentation methods…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Yang-Che Sun , Cheng Sun , Chin-Yang Lin , Fu-En Yang , Min-Hung Chen , Yen-Yu Lin , Yu-Lun Liu