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Understanding how humans interact with each other is key to building realistic multi-human virtual reality systems. This area remains relatively unexplored due to the lack of large-scale datasets. Recent datasets focusing on this issue…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Rawal Khirodkar , Jyun-Ting Song , Jinkun Cao , Zhengyi Luo , Kris Kitani

Despite significant advancements in dynamic neural rendering, existing methods fail to address the unique challenges posed by UAV-captured scenarios, particularly those involving monocular camera setups, top-down perspective, and multiple…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Jaehoon Choi , Dongki Jung , Christopher Maxey , Yonghan Lee , Sungmin Eum , Dinesh Manocha , Heesung Kwon

We propose the problem of point-level 3D scene interpolation, which aims to simultaneously reconstruct a 3D scene in two states from multiple views, synthesize smooth point-level interpolations between them, and render the scene from novel…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Shichong Peng , Yanshu Zhang , Ke Li

Modeling human-scene interactions (HSI) is essential for understanding and simulating everyday human behaviors. Recent approaches utilizing generative modeling have made progress in this domain; however, they are limited in controllability…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Inwoo Hwang , Bing Zhou , Young Min Kim , Jian Wang , Chuan Guo

3D human avatar animation aims at transforming a human avatar from an arbitrary initial pose to a specified target pose using deformation algorithms. Existing approaches typically divide this task into two stages: canonical template…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Jian Shu , Nanjie Yao , Gangjian Zhang , Junlong Ren , Yu Feng , Hao Wang

We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable indoor scenes. Unlike prior text-driven methods that often suffer from geometric drift or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Stefan Ainetter , Thomas Deixelberger , Edoardo A. Dominici , Philipp Drescher , Konstantinos Vardis , Markus Steinberger

Recent advances in illumination control extend image-based methods to video, yet still facing a trade-off between lighting fidelity and temporal consistency. Moving beyond relighting, a key step toward generative modeling of real-world…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Tianqi Liu , Zhaoxi Chen , Zihao Huang , Shaocong Xu , Saining Zhang , Chongjie Ye , Bohan Li , Zhiguo Cao , Wei Li , Hao Zhao , Ziwei Liu

Scenes are continuously undergoing dynamic changes in the real world. However, existing human-scene interaction generation methods typically treat the scene as static, which deviates from reality. Inspired by world models, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yin Wang , Zhiying Leng , Haitian Liu , Frederick W. B. Li , Mu Li , Xiaohui Liang

Controllable character image animation has a wide range of applications. Although existing studies have consistently improved performance, challenges persist in the field of character image animation, particularly concerning stability in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Jingyun Xue , Hongfa Wang , Qi Tian , Yue Ma , Andong Wang , Zhiyuan Zhao , Shaobo Min , Wenzhe Zhao , Kaihao Zhang , Heung-Yeung Shum , Wei Liu , Mengyang Liu , Wenhan Luo

Synthesizing interactive 3D scenes from text is essential for gaming, virtual reality, and embodied AI. However, existing methods face several challenges. Learning-based approaches depend on small-scale indoor datasets, limiting the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Lu Ling , Chen-Hsuan Lin , Tsung-Yi Lin , Yifan Ding , Yu Zeng , Yichen Sheng , Yunhao Ge , Ming-Yu Liu , Aniket Bera , Zhaoshuo Li

Current methods for dense 3D point tracking in dynamic scenes typically rely on pairwise processing, require known camera poses, or assume temporal ordering of input frames, thereby constraining their flexibility and applicability.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Vivek Alumootil , Tuan-Anh Vu

Multi-view video reconstruction plays a vital role in computer vision, enabling applications in film production, virtual reality, and motion analysis. While recent advances such as 4D Gaussian Splatting (4DGS) have demonstrated impressive…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Zhixin Xu , Hengyu Zhou , Yuan Liu , Wenhan Xue , Hao Pan , Wenping Wang , Bin Wang

High fidelity digital 3D environments have been proposed in recent years, however, it remains extremely challenging to automatically equip such environment with realistic human bodies. Existing work utilizes images, depth or semantic maps…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Siwei Zhang , Yan Zhang , Qianli Ma , Michael J. Black , Siyu Tang

We introduce LivingWorld, an interactive framework for generating 4D worlds with environmental dynamics from a single image. While recent advances in 3D scene generation enable large-scale environment creation, most approaches focus…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Hyeongju Mun , In-Hwan Jin , Sohyeong Kim , Kyeongbo Kong

Preserving first-frame identity while ensuring precise motion control is a fundamental challenge in human image animation. The Image-to-Motion Binding process of the dominant Reference-to-Video (R2V) paradigm overlooks critical…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jiaming Zhang , Shengming Cao , Rui Li , Xiaotong Zhao , Yutao Cui , Xinglin Hou , Gangshan Wu , Haolan Chen , Yu Xu , Limin Wang , Kai Ma

Reconstructing dense, volumetric models of real-world 3D scenes is important for many tasks, but capturing large scenes can take significant time, and the risk of transient changes to the scene goes up as the capture time increases. These…

Computer Vision and Pattern Recognition · Computer Science 2019-07-03 Stuart Golodetz , Tommaso Cavallari , Nicholas A Lord , Victor A Prisacariu , David W Murray , Philip H S Torr

Recovering high-quality 3D human motion in complex scenes from monocular videos is important for many applications, ranging from AR/VR to robotics. However, capturing realistic human-scene interactions, while dealing with occlusions and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-25 Siwei Zhang , Yan Zhang , Federica Bogo , Marc Pollefeys , Siyu Tang

In this paper, we propose PixelHuman, a novel human rendering model that generates animatable human scenes from a few images of a person with unseen identity, views, and poses. Previous work have demonstrated reasonable performance in novel…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Gyumin Shim , Jaeseong Lee , Junha Hyung , Jaegul Choo

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

Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regularization or feed-forward deterministic model) to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hanyang Wang , Fangfu Liu , Jiawei Chi , Yueqi Duan
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