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Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent systems. Recent approaches have improved temporal coherence…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Melonie de Almeida , Daniela Ivanova , Tong Shi , John H. Williamson , Paul Henderson

This paper presents DENSER, an efficient and effective approach leveraging 3D Gaussian splatting (3DGS) for the reconstruction of dynamic urban environments. While several methods for photorealistic scene representations, both implicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Mahmud A. Mohamad , Gamal Elghazaly , Arthur Hubert , Raphael Frank

Robotic manipulation systems operating in complex environments rely on perception systems that provide information about the geometry (pose and 3D shape) of the objects in the scene along with other semantic information such as object…

Robotics · Computer Science 2023-05-17 Shubham Agrawal , Nikhil Chavan-Dafle , Isaac Kasahara , Selim Engin , Jinwook Huh , Volkan Isler

We consider the problem of editing 3D objects and scenes based on open-ended language instructions. A common approach to this problem is to use a 2D image generator or editor to guide the 3D editing process, obviating the need for 3D data.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Minghao Chen , Iro Laina , Andrea Vedaldi

Recent 4D dynamic scene editing methods require editing thousands of 2D images used for dynamic scene synthesis and updating the entire scene with additional training loops, resulting in several hours of processing to edit a single dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Joohyun Kwon , Hanbyel Cho , Junmo Kim

The shape of an object is an important characteristic for many vision problems such as segmentation, detection and tracking. Being independent of appearance, it is possible to generalize to a large range of objects from only small amounts…

Machine Learning · Statistics 2018-12-14 Alessandro Di Martino , Erik Bodin , Carl Henrik Ek , Neill D. F. Campbell

Recent advances in 3D Gaussian Splatting (3DGS) have achieved state-of-the-art results for novel view synthesis. However, efficiently capturing high-fidelity reconstructions of specific objects within complex scenes remains a significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Haiyi Li , Qi Chen , Denis Kalkofen , Hsiang-Ting Chen

This research tackles the challenge of real-time active view selection and uncertainty quantification on visual quality for active 3D reconstruction. Visual quality is a critical aspect of 3D reconstruction. Recent advancements such as…

Graphics · Computer Science 2025-05-01 Yuhan Xie , Yixi Cai , Yinqiang Zhang , Lei Yang , Jia Pan

Reconstructing and predicting dynamic 3D scenes from multi-view videos is a foundational task for robotics, AR/VR, and digital twins. Recent physics-informed Gaussian Splatting methods achieve impressive future frame extrapolation but lack…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Denis Gridusov , Maxim Popov , Sergey Kolyubin

3D Gaussian Splatting is renowned for its high-fidelity reconstructions and real-time novel view synthesis, yet its lack of semantic understanding limits object-level perception. In this work, we propose ObjectGS, an object-aware framework…

Graphics · Computer Science 2025-07-22 Ruijie Zhu , Mulin Yu , Linning Xu , Lihan Jiang , Yixuan Li , Tianzhu Zhang , Jiangmiao Pang , Bo Dai

Motion segmentation in dynamic scenes is highly challenging, as conventional methods heavily rely on estimating camera poses and point correspondences from inherently noisy motion cues. Existing statistical inference or iterative…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Xiankang He , Peile Lin , Ying Cui , Dongyan Guo , Chunhua Shen , Xiaoqin Zhang

Accurately reconstructing a 3D scene including explicit geometry information is both attractive and challenging. Geometry reconstruction can benefit from incorporating differentiable appearance models, such as Neural Radiance Fields and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Ancheng Lin , Yusheng Xiang , Paul Kennedy , Jun Li

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently, Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Yi-Hua Huang , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

Reconstructing dynamic driving scenes is essential for developing autonomous systems through sensor-realistic simulation. Although recent methods achieve high-fidelity reconstructions, they either rely on costly human annotations for object…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Carl Lindström , Mahan Rafidashti , Maryam Fatemi , Lars Hammarstrand , Martin R. Oswald , Lennart Svensson

To reach human performance on complex tasks, a key ability for artificial systems is to understand physical interactions between objects, and predict future outcomes of a situation. This ability, often referred to as intuitive physics, has…

Computer Vision and Pattern Recognition · Computer Science 2020-05-04 Ronan Riochet , Josef Sivic , Ivan Laptev , Emmanuel Dupoux

Teaching robots to fold, drape, or reposition deformable objects such as cloth will unlock a variety of automation applications. While remarkable progress has been made for rigid object manipulation, manipulating deformable objects poses…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Bardienus P. Duisterhof , Zhao Mandi , Yunchao Yao , Jia-Wei Liu , Jenny Seidenschwarz , Mike Zheng Shou , Deva Ramanan , Shuran Song , Stan Birchfield , Bowen Wen , Jeffrey Ichnowski

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

Urban scene reconstruction is crucial for real-world autonomous driving simulators. Although existing methods have achieved photorealistic reconstruction, they mostly focus on pinhole cameras and neglect fisheye cameras. In fact, how to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yuan Ren , Guile Wu , Runhao Li , Zheyuan Yang , Yibo Liu , Xingxin Chen , Tongtong Cao , Bingbing Liu

We introduce PhysMotion, a novel framework that leverages principled physics-based simulations to guide intermediate 3D representations generated from a single image and input conditions (e.g., applied force and torque), producing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Xiyang Tan , Ying Jiang , Xuan Li , Zeshun Zong , Tianyi Xie , Yin Yang , Chenfanfu Jiang

We present GaussianAvatar, an efficient approach to creating realistic human avatars with dynamic 3D appearances from a single video. We start by introducing animatable 3D Gaussians to explicitly represent humans in various poses and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Liangxiao Hu , Hongwen Zhang , Yuxiang Zhang , Boyao Zhou , Boning Liu , Shengping Zhang , Liqiang Nie