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In addition to color and textural information, geometry provides important cues for 3D scene reconstruction. However, current reconstruction methods only include geometry at the feature level thus not fully exploiting the geometric…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Ruihong Yin , Sezer Karaoglu , Theo Gevers

Due to the visual properties of reflection and refraction, RGB-D cameras cannot accurately capture the depth of transparent objects, leading to incomplete depth maps. To fill in the missing points, recent studies tend to explore new visual…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Yiheng Huang , Junhong Chen , Nick Michiels , Muhammad Asim , Luc Claesen , Wenyin Liu

The advancement of generative radiance fields has pushed the boundary of 3D-aware image synthesis. Motivated by the observation that a 3D object should look realistic from multiple viewpoints, these methods introduce a multi-view constraint…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Xingang Pan , Xudong Xu , Chen Change Loy , Christian Theobalt , Bo Dai

Recently, deep learning-based 3D face reconstruction methods have demonstrated promising advancements in terms of quality and efficiency. Nevertheless, these techniques face challenges in effectively handling occluded scenes and fail to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Dapeng Zhao

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetric nature of 3DGS limits its ability to accurately capture surface geometry. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Prajwal Gupta C. R. , Divyam Sheth , Jinjoo Ha , Mirela Ostrek , Justus Thies

Current RGB-based 6D object pose estimation methods have achieved noticeable performance on datasets and real world applications. However, predicting 6D pose from single 2D image features is susceptible to disturbance from changing of…

Computer Vision and Pattern Recognition · Computer Science 2022-07-04 Jun Wu , Lilu Liu , Yue Wang , Rong Xiong

Recent advances in 3D Gaussian Splatting (3D-GS) have shown remarkable success in representing 3D scenes and generating high-quality, novel views in real-time. However, 3D-GS and its variants assume that input images are captured based on…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Liao Shen , Tianqi Liu , Huiqiang Sun , Jiaqi Li , Zhiguo Cao , Wei Li , Chen Change Loy

Recent advances in radiance fields and novel view synthesis enable creation of realistic digital twins from photographs. However, current methods struggle with flat, texture-less surfaces, creating uneven and semi-transparent…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Maria Taktasheva , Lily Goli , Alessandro Fiorini , Zhen Li , Daniel Rebain , Andrea Tagliasacchi

Transferring appearance to 3D assets using different representations of the appearance object - such as images or text - has garnered interest due to its wide range of applications in industries like gaming, augmented reality, and digital…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Sayan Deb Sarkar , Sinisa Stekovic , Vincent Lepetit , Iro Armeni

Real-time reconstruction of deformable surgical scenes is vital for advancing robotic surgery, improving surgeon guidance, and enabling automation. Recent methods achieve dense reconstructions from da Vinci robotic surgery videos, with…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Tianyi Song , Danail Stoyanov , Evangelos Mazomenos , Francisco Vasconcelos

We address the problem of generating a 360-degree image from a single image with a narrow field of view by estimating its surroundings. Previous methods suffered from overfitting to the training resolution and deterministic generation. This…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Naofumi Akimoto , Yuhi Matsuo , Yoshimitsu Aoki

LiDAR depth completion is a task that predicts depth values for every pixel on the corresponding camera frame, although only sparse LiDAR points are available. Most of the existing state-of-the-art solutions are based on deep neural…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Yiming Zhao , Lin Bai , Ziming Zhang , Xinming Huang

3D Gaussian Splatting (3DGS) has shown a powerful capability for novel view synthesis due to its detailed expressive ability and highly efficient rendering speed. Unfortunately, creating relightable 3D assets and reconstructing faithful…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Zuo-Liang Zhu , Beibei Wang , Jian Yang

We propose an approach for 3D reconstruction and segmentation of a single object placed on a flat surface from an input video. Our approach is to perform dense depth map estimation for multiple views using a proposed objective function that…

Computer Vision and Pattern Recognition · Computer Science 2016-07-29 Tanmay Gupta , Daeyun Shin , Naren Sivagnanadasan , Derek Hoiem

This paper focuses on a challenging setting of simultaneously modeling geometry and appearance of hand-object interaction scenes without any object priors. We follow the trend of dynamic 3D Gaussian Splatting based methods, and address…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hao Tian , Chenyangguang Zhang , Rui Liu , Wen Shen , Xiaolin Qin

In 3D reconstruction of underwater scenes, traditional methods based on atmospheric optical models cannot effectively deal with the selective attenuation of light wavelengths and the effect of suspended particle scattering, which are unique…

Graphics · Computer Science 2025-08-14 Jiachen Li , Guangzhi Han , Jin Wan , Yuan Gao , Delong Han

3D semantic occupancy prediction requires accurate 2D-to-3D feature lifting, yet current methods restrict camera geometry to initial projections. Subsequent operations like offset learning, attention weighting, and cross-camera aggregation…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Xun Chen , Tianchen Deng , Rui Wang , Fangjinhua Wang , Junyi Ma , Hongming Shen , Hesheng Wang , Danwei Wang

In this paper, we introduce a novel approach that harnesses both 2D and 3D attentions to enable highly accurate depth completion without requiring iterative spatial propagations. Specifically, we first enhance a baseline convolutional depth…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Yunxiao Shi , Manish Kumar Singh , Hong Cai , Fatih Porikli

3D Gaussian Splatting has recently emerged as an efficient solution for high-quality and real-time novel view synthesis. However, its capability for accurate surface reconstruction remains underexplored. Due to the discrete and unstructured…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Qing Li , Huifang Feng , Xun Gong , Yu-Shen Liu

This paper presents a comprehensive pipeline for recognizing objects targeted by human pointing gestures using RGB images. As human-robot interaction moves toward more intuitive interfaces, the ability to identify targets of non-verbal…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Lukáš Hajdúch , Viktor Kocur