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Recent 3D-based manipulation methods either directly predict the grasp pose using 3D neural networks, or solve the grasp pose using similar objects retrieved from shape databases. However, the former faces generalizability challenges when…

Robotics · Computer Science 2023-10-03 Luobin Wang , Runlin Guo , Quan Vuong , Yuzhe Qin , Hao Su , Henrik Christensen

Inverse rendering aims to estimate physical attributes of a scene, e.g., reflectance, geometry, and lighting, from image(s). Inverse rendering has been studied primarily for single objects or with methods that solve for only one of the…

Computer Vision and Pattern Recognition · Computer Science 2019-09-17 Soumyadip Sengupta , Jinwei Gu , Kihwan Kim , Guilin Liu , David W. Jacobs , Jan Kautz

We provide a deterministic channel model for a scenario where wireless connectivity is established through a reflection from a planar smooth surface of an infinite extent. The developed model is rigorously built upon the physics of wave…

Information Theory · Computer Science 2022-05-04 Andrea Pizzo , Angel Lozano , Sundeep Rangan , Thomas Marzetta

Mobile robots operating indoors must be prepared to navigate challenging scenes that contain transparent surfaces. This paper proposes a novel method for the fusion of acoustic and visual sensing modalities through implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Advaith V. Sethuraman , Onur Bagoren , Harikrishnan Seetharaman , Dalton Richardson , Joseph Taylor , Katherine A. Skinner

3D scene reconstruction from 2D images has been a long-standing task. Instead of estimating per-frame depth maps and fusing them in 3D, recent research leverages the neural implicit surface as a unified representation for 3D reconstruction.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Xinyi Yu , Liqin Lu , Jintao Rong , Guangkai Xu , Linlin Ou

City-scale 3D surface reconstruction from multiview images for downstream 3D simulation, poses highly challenging problems due to the scale and complexity of urban scenes. Existing city-scale 3D reconstruction methods based on NeRF,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Sayan Paul , Sourav Ghosh , Siddharth Katageri , Soumyadip Maity , Sanjana Sinha , Brojeshwar Bhowmick

Event-based video reconstruction has garnered increasing attention due to its advantages, such as high dynamic range and rapid motion capture capabilities. However, current methods often prioritize the extraction of temporal information…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Lin Zhu , Yunlong Zheng , Yijun Zhang , Xiao Wang , Lizhi Wang , Hua Huang

The emergence of neural and Gaussian-based radiance field methods has led to considerable advancements in novel view synthesis and 3D object reconstruction. Nonetheless, specular reflection and refraction continue to pose significant…

Graphics · Computer Science 2025-05-02 Letian Huang , Dongwei Ye , Jialin Dan , Chengzhi Tao , Huiwen Liu , Kun Zhou , Bo Ren , Yuanqi Li , Yanwen Guo , Jie Guo

What's the most accurate 3D model of your face you can obtain while sitting at your desk? We attempt to answer this question in our work. High fidelity face reconstructions have so far been limited to either studio settings or through…

Computer Vision and Pattern Recognition · Computer Science 2020-03-20 Shubham Agrawal , Anuj Pahuja , Simon Lucey

We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed distance fields and post-hoc layout optimization, PixARMesh…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xiang Zhang , Sohyun Yoo , Hongrui Wu , Chuan Li , Jianwen Xie , Zhuowen Tu

We propose a method to realistically insert synthetic objects into existing photographs without requiring access to the scene or any additional scene measurements. With a single image and a small amount of annotation, our method creates a…

Graphics · Computer Science 2019-12-30 Kevin Karsch , Varsha Hedau , David Forsyth , Derek Hoiem

We propose TensoIR, a novel inverse rendering approach based on tensor factorization and neural fields. Unlike previous works that use purely MLP-based neural fields, thus suffering from low capacity and high computation costs, we extend…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Haian Jin , Isabella Liu , Peijia Xu , Xiaoshuai Zhang , Songfang Han , Sai Bi , Xiaowei Zhou , Zexiang Xu , Hao Su

We propose RelitLRM, a Large Reconstruction Model (LRM) for generating high-quality Gaussian splatting representations of 3D objects under novel illuminations from sparse (4-8) posed images captured under unknown static lighting. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Tianyuan Zhang , Zhengfei Kuang , Haian Jin , Zexiang Xu , Sai Bi , Hao Tan , He Zhang , Yiwei Hu , Milos Hasan , William T. Freeman , Kai Zhang , Fujun Luan

In this paper we present a new methodology for edge detection in digital images. The first originality of the proposed method is to consider image content as a parametric surface. Then, an original parametric local model of this surface…

Image and Video Processing · Electrical Eng. & Systems 2019-04-24 Rémi Cogranne , Rémi Slysz , Laurence Moreau , Houman Borouchaki

Rendering novel view images is highly desirable for many applications. Despite recent progress, it remains challenging to render high-fidelity and view-consistent novel views of large-scale scenes from in-the-wild images with inevitable…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Peng Dai , Yinda Zhang , Xin Yu , Xiaoyang Lyu , Xiaojuan Qi

Neural Radiance Fields (NeRF) have shown impressive performance in novel view synthesis, but challenges remain in rendering scenes with complex specular reflections and highlights. Existing approaches may produce blurry reflections due to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Wenpeng Xing , Jie Chen , Zaifeng Yang , Tiancheng Zhao , Gaolei Li , Changting Lin , Yike Guo , Meng Han

We present a physics-based inverse rendering method that learns the illumination, geometry, and materials of a scene from posed multi-view RGB images. To model the illumination of a scene, existing inverse rendering works either completely…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Youming Deng , Xueting Li , Sifei Liu , Ming-Hsuan Yang

With the support of Virtual Reality (VR) and Augmented Reality (AR) technologies, the 3D virtual eyeglasses try-on application is well on its way to becoming a new trending solution that offers a "try on" option to select the perfect pair…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Fan Zhang , Ziyue Ji , Weiguang Kang , Weiqing Li , Zhiyong Su

Deep learning based rendering has achieved major improvements in photo-realistic image synthesis, with potential applications including visual effects in movies and photo-realistic scene building in video games. However, a significant…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Zhuo He , Paul Henderson , Nicolas Pugeault

Video inpainting tasks have seen significant improvements in recent years with the rise of deep neural networks and, in particular, vision transformers. Although these models show promising reconstruction quality and temporal consistency,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Guillaume Thiry , Hao Tang , Radu Timofte , Luc Van Gool
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