activity
20162026
most citedDeep Continuous Fusion for Multi-Sensor 3D Object Detection

430 citations · 994 across the 68 of their papers we have counts for

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Showing 2025 · cs.CVShow all

13 papers · 2 filters

cs.CV2025

SceneDiff: A Benchmark and Method for Multiview Object Change Detection

Yuqun Wu, Chih-hao Lin, Henry Che +4

We investigate the problem of identifying objects that have been added, removed, or moved between a pair of captures (images or videos) of the same scene at different times. Accura…

cs.CV2025

Visual Sync: Multi-Camera Synchronization via Cross-View Object Motion

Shaowei Liu, David Yifan Yao, Saurabh Gupta +1

Today, people can easily record memorable moments, ranging from concerts, sports events, lectures, family gatherings, and birthday parties with multiple consumer cameras. However,…

cs.CV2025

NoPo-Avatar: Generalizable and Animatable Avatars from Sparse Inputs without Human Poses

Jing Wen, Alexander G. Schwing, Shenlong Wang

We tackle the task of recovering an animatable 3D human avatar from a single or a sparse set of images. For this task, beyond a set of images, many prior state-of-the-art methods u…

cs.CV2025

Demeter: A Parametric Model of Crop Plant Morphology from the Real World

Tianhang Cheng, Albert J. Zhai, Evan Z. Chen +13

Learning 3D parametric shape models of objects has gained popularity in vision and graphics and has showed broad utility in 3D reconstruction, generation, understanding, and simula…

cs.CV2025

HoloScene: Simulation-Ready Interactive 3D Worlds from a Single Video

Hongchi Xia, Chih-Hao Lin, Hao-Yu Hsu +5

Digitizing the physical world into accurate simulation-ready virtual environments offers significant opportunities in a variety of fields such as augmented and virtual reality, gam…

cs.CV2025

AD-GS: Object-Aware B-Spline Gaussian Splatting for Self-Supervised Autonomous Driving

Jiawei Xu, Kai Deng, Zexin Fan +3

Modeling and rendering dynamic urban driving scenes is crucial for self-driving simulation. Current high-quality methods typically rely on costly manual object tracklet annotations…