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Unsupervised learning of object-centric representations in dynamic visual scenes is challenging. Unlike most previous approaches that learn to decompose 2D images, we present DynaVol, a 3D scene generative model that unifies geometric…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Yanpeng Zhao , Siyu Gao , Yunbo Wang , Xiaokang Yang

The increasing demand for immersive AR/VR applications and spatial intelligence has heightened the need to generate high-quality scene-level and 360${\deg}$ panoramic video. However, most video diffusion models are constrained by limited…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Jinxiu Liu , Shaoheng Lin , Yinxiao Li , Ming-Hsuan Yang

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

Disparity/depth estimation from sequences of stereo images is an important element in 3D vision. Owing to occlusions, imperfect settings and homogeneous luminance, accurate estimate of depth remains a challenging problem. Targetting view…

Image and Video Processing · Electrical Eng. & Systems 2020-03-17 Nantheera Anantrasirichai , Majid Geravand , David Braendler , David R. Bull

Visual SLAM algorithms have been enhanced through the exploration of Gaussian Splatting representations, particularly in generating high-fidelity dense maps. While existing methods perform reliably in static environments, they often…

Robotics · Computer Science 2025-09-03 Yi Liu , Keyu Fan , Bin Lan , Houde Liu

Recent advances in deep learning methods have increased the performance of face detection and recognition systems. The accuracy of these models relies on the range of variation provided in the training data. Creating a dataset that…

Computer Vision and Pattern Recognition · Computer Science 2020-06-23 Shubhajit Basak , Hossein Javidnia , Faisal Khan , Rachel McDonnell , Michael Schukat

Novel view synthesis (NVS) from a single image is highly ill-posed due to large unobserved regions, especially for views that deviate significantly from the input. While existing methods focus on consistency between the source and generated…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Xueyang Kang , Zhengkang Xiang , Zezheng Zhang , Kourosh Khoshelham

We present BetterScene, an approach to enhance novel view synthesis (NVS) quality for diverse real-world scenes using extremely sparse, unconstrained photos. BetterScene leverages the production-ready Stable Video Diffusion (SVD) model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Yuci Han , Charles Toth , John E. Anderson , William J. Shuart , Alper Yilmaz

Videos from edited media like movies are a useful, yet under-explored source of information. The rich variety of appearance and interactions between humans depicted over a large temporal context in these films could be a valuable source of…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Georgios Pavlakos , Jitendra Malik , Angjoo Kanazawa

Recent advancements in generative models have provided promising solutions for synthesizing realistic driving videos, which are crucial for training autonomous driving perception models. However, existing approaches often struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Wei Wu , Xi Guo , Weixuan Tang , Tingxuan Huang , Chiyu Wang , Dongyue Chen , Chenjing Ding

We present a practical and robust deep learning solution for capturing and rendering novel views of complex real world scenes for virtual exploration. Previous approaches either require intractably dense view sampling or provide little to…

Computer Vision and Pattern Recognition · Computer Science 2019-05-03 Ben Mildenhall , Pratul P. Srinivasan , Rodrigo Ortiz-Cayon , Nima Khademi Kalantari , Ravi Ramamoorthi , Ren Ng , Abhishek Kar

We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video. Our method builds up on coarse 4D surface reconstructions, as obtained with commonly used…

Computer Vision and Pattern Recognition · Computer Science 2016-02-08 Nadia Robertini , Edilson De Aguiar , Thomas Helten , Christian Theobalt

We explore novel-view synthesis for dynamic scenes from monocular videos. Prior approaches rely on costly test-time optimization of 4D representations or do not preserve scene geometry when trained in a feed-forward manner. Our approach is…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Kaihua Chen , Tarasha Khurana , Deva Ramanan

Remote telepresence via next-generation mixed reality platforms can provide higher levels of immersion for computer-mediated communications, allowing participants to engage in a wide spectrum of activities, previously not possible in 2D…

Human-Computer Interaction · Computer Science 2022-04-04 Mohammad Keshavarzi , Michael Zollhoefer , Allen Y. Yang , Patrick Peluse , Luisa Caldas

Domain scientists often face I/O and storage challenges when keeping raw data from large-scale simulations. Saving visualization images, albeit practical, is limited to preselected viewpoints, transfer functions, and simulation parameters.…

Graphics · Computer Science 2025-02-25 Siyuan Yao , Yunfei Lu , Chaoli Wang

We consider the problem of reconstructing a dynamic scene observed from a stereo camera. Most existing methods for depth from stereo treat different stereo frames independently, leading to temporally inconsistent depth predictions. Temporal…

Computer Vision and Pattern Recognition · Computer Science 2023-05-04 Nikita Karaev , Ignacio Rocco , Benjamin Graham , Natalia Neverova , Andrea Vedaldi , Christian Rupprecht

Recent years have witnessed a rapid development of immersive multimedia which bridges the gap between the real world and virtual space. Volumetric videos, as an emerging representative 3D video paradigm that empowers extended reality, stand…

Multimedia · Computer Science 2023-04-18 Kaiyuan Hu , Yili Jin , Haowen Yang , Junhua Liu , Fangxin Wang

State-of-the-art novel view synthesis methods achieve impressive results for multi-view captures of static 3D scenes. However, the reconstructed scenes still lack "liveliness," a key component for creating engaging 3D experiences. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Thomas Wimmer , Michael Oechsle , Michael Niemeyer , Federico Tombari

Generating high-quality camera-controllable videos from monocular input is a challenging task, particularly under extreme viewpoint. Existing methods often struggle with geometric inconsistencies and occlusion artifacts in boundaries,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Tao Hu , Haoyang Peng , Xiao Liu , Yuewen Ma

We introduce VividDream, a method for generating explorable 4D scenes with ambient dynamics from a single input image or text prompt. VividDream first expands an input image into a static 3D point cloud through iterative inpainting and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Yao-Chih Lee , Yi-Ting Chen , Andrew Wang , Ting-Hsuan Liao , Brandon Y. Feng , Jia-Bin Huang