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Event cameras produce asynchronous event streams that are spatially sparse yet temporally dense. Mainstream event representation learning algorithms typically use event frames, voxels, or tensors as input. Although these approaches have…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Futian Wang , Fan Zhang , Xiao Wang , Mengqi Wang , Dexing Huang , Jin Tang

Event cameras, mimicking the human retina, capture brightness changes with unparalleled temporal resolution and dynamic range. Integrating events into intensities poses a highly ill-posed challenge, marred by initial condition ambiguities.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Jinxiu Liang , Bohan Yu , Yixin Yang , Yiming Han , Boxin Shi

Dynamic scenes rendering is an intriguing yet challenging problem. Although current methods based on NeRF have achieved satisfactory performance, they still can not reach real-time levels. Recently, 3D Gaussian Splatting (3DGS) has garnered…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Jiahao Lu , Jiacheng Deng , Ruijie Zhu , Yanzhe Liang , Wenfei Yang , Tianzhu Zhang , Xu Zhou

Reconstructing sharp 3D representations from blurry multi-view images are long-standing problem in computer vision. Recent works attempt to enhance high-quality novel view synthesis from the motion blur by leveraging event-based cameras,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Seungjun Lee , Gim Hee Lee

Gaussian Splatting (GS) and Neural Radiance Fields (NeRF) are two groundbreaking technologies that have revolutionized the field of Novel View Synthesis (NVS), enabling immersive photorealistic rendering and user experiences by synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2025-01-15 Yuhang Zhang , Joshua Maraval , Zhengyu Zhang , Nicolas Ramin , Shishun Tian , Lu Zhang

Novel view synthesis is a task of generating scenes from unseen perspectives; however, synthesizing dynamic scenes from blurry monocular videos remains an unresolved challenge that has yet to be effectively addressed. Existing novel view…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Yeon-Ji Song , Jaein Kim , Byung-Ju Kim , Byoung-Tak Zhang

Edge vision systems combining sensing and embedded processing promise low-latency, decentralized, and energy-efficient solutions that forgo reliance on the cloud. As opposed to conventional frame-based vision sensors, event-based cameras…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Yufeng Yang , Adrian Kneip , Charlotte Frenkel

3D deblurring reconstruction techniques have recently seen significant advancements with the development of Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS). Although these techniques can recover relatively clear 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Yuchen Weng , Zhengwen Shen , Ruofan Chen , Qi Wang , Jun Wang

Novel-view synthesis (NVS) can be tackled through different approaches, depending on the general setting: a single source image to a short video sequence, exact or noisy camera pose information, 3D-based information such as point clouds…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Gaétan Landreau , Mohamed Tamaazousti

Event cameras are neuromorphic vision sensors that record a scene as sparse and asynchronous event streams. Most event-based methods project events into dense frames and process them using conventional vision models, resulting in high…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Bochen Xie , Yongjian Deng , Zhanpeng Shao , Qingsong Xu , Youfu Li

We present a method for generating consistent novel views from a single source image. Our approach focuses on maximizing the reuse of visible pixels from the source image. To achieve this, we use a monocular depth estimator that transfers…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Yash Kant , Aliaksandr Siarohin , Michael Vasilkovsky , Riza Alp Guler , Jian Ren , Sergey Tulyakov , Igor Gilitschenski

Existing methods for 3D tracking from monocular RGB videos predominantly consider articulated and rigid objects. Modelling dense non-rigid object deformations in this setting remained largely unaddressed so far, although such effects can…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Soshi Shimada , Vladislav Golyanik , Patrick Pérez , 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

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since -- without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Edith Tretschk , Navami Kairanda , Mallikarjun B R , Rishabh Dabral , Adam Kortylewski , Bernhard Egger , Marc Habermann , Pascal Fua , Christian Theobalt , Vladislav Golyanik

Novel View Synthesis plays a crucial role by generating new 2D renderings from multi-view images of 3D scenes. However, capturing high-speed scenes with conventional cameras often leads to motion blur, hindering the effectiveness of 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jiyuan Zhang , Kang Chen , Shiyan Chen , Yajing Zheng , Tiejun Huang , Zhaofei Yu

Reconstructing large-scale dynamic scenes from visual observations is a fundamental challenge in computer vision, with critical implications for robotics and autonomous systems. While recent differentiable rendering methods such as Neural…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Jingkang Wang , Henry Che , Yun Chen , Ze Yang , Lily Goli , Sivabalan Manivasagam , Raquel Urtasun

4D millimeter-wave radar is a promising sensing modality for autonomous driving, yet effective 3D object detection from 4D radar and monocular images remains challenging. Existing fusion approaches either rely on instance proposals lacking…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Xiaokai Bai , Chenxu Zhou , Lianqing Zheng , Si-Yuan Cao , Jianan Liu , Xiaohan Zhang , Yiming Li , Zhengzhuang Zhang , Hui-liang Shen

Novel view synthesis (NVS) has shown significant promise for applications in cinematographic production, particularly through the exploitation of Neural Radiance Fields (NeRF) and Gaussian Splatting (GS). These methods model real 3D scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Adrian Azzarelli , Nantheera Anantrasirichai , David R Bull

High dynamic range (HDR) novel view synthesis (NVS) aims to create photorealistic images from novel viewpoints using HDR imaging techniques. The rendered HDR images capture a wider range of brightness levels containing more details of the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Yuanhao Cai , Zihao Xiao , Yixun Liang , Minghan Qin , Yulun Zhang , Xiaokang Yang , Yaoyao Liu , Alan Yuille

Event cameras are bio-inspired sensors that capture the per-pixel intensity changes asynchronously and produce event streams encoding the time, pixel position, and polarity (sign) of the intensity changes. Event cameras possess a myriad of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Xu Zheng , Yexin Liu , Yunfan Lu , Tongyan Hua , Tianbo Pan , Weiming Zhang , Dacheng Tao , Lin Wang