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Articulated objects like cabinets and doors are widespread in daily life. However, directly manipulating 3D articulated objects is challenging because they have diverse geometrical shapes, semantic categories, and kinetic constraints. Prior…

Robotics · Computer Science 2024-03-04 Qiaojun Yu , Junbo Wang , Wenhai Liu , Ce Hao , Liu Liu , Lin Shao , Weiming Wang , Cewu Lu

Neural Radiance Fields (NeRF) has emerged as a compelling framework for scene representation and 3D recovery. To improve its performance on real-world data, depth regularizations have proven to be the most effective ones. However, depth…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Aoxiang Fan , Corentin Dumery , Nicolas Talabot , Pascal Fua

3D Gaussian Splatting (3DGS) has recently emerged as a powerful paradigm for photorealistic view synthesis, representing scenes with spatially distributed Gaussian primitives. While highly effective for rendering, achieving accurate and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Wenzhi Guo , Bing Wang

Neural rendering methods can achieve near-photorealistic image synthesis of scenes from posed input images. However, when the images are imperfect, e.g., captured in very low-light conditions, state-of-the-art methods fail to reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Vinayak Gupta , Rongali Simhachala Venkata Girish , Mukund Varma T , Ayush Tewari , Kaushik Mitra

Recently, Neural Radiance Fields (NeRF) achieved impressive results in novel view synthesis. Block-NeRF showed the capability of leveraging NeRF to build large city-scale models. For large-scale modeling, a mass of image data is necessary.…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Tong Qin , Changze Li , Haoyang Ye , Shaowei Wan , Minzhen Li , Hongwei Liu , Ming Yang

We present a simple yet powerful neural network that implicitly represents and renders 3D objects and scenes only from 2D observations. The network models 3D geometries as a general radiance field, which takes a set of 2D images with camera…

Computer Vision and Pattern Recognition · Computer Science 2021-08-12 Alex Trevithick , Bo Yang

Identification of cracks is essential to assess the structural integrity of concrete infrastructure. However, robust crack segmentation remains a challenging task for computer vision systems due to the diverse appearance of concrete…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Achref Jaziri , Martin Mundt , Andres Fernandez Rodriguez , Visvanathan Ramesh

Analytical Dark Field Scanning Transmission Electron Microscopy (ADF-STEM) tomography reconstructs nanoscale materials in 3D by integrating multi-view tilt-series images, enabling precise analysis of their structural and compositional…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Beiyuan Zhang , Hesong Li , Ruiwen Shao , Ying Fu

Long-term vertebral fractures severely affect the life quality of patients, causing kyphotic, lumbar deformity and even paralysis. Computed tomography (CT) is a common clinical examination to screen for this disease at early stages.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-14 Xin Wei , Huaiwei Cong , Zheng Zhang , Junran Peng , Guoping Chen , Jinpeng Li

Robot assembly discovery is a challenging problem that lives at the intersection of resource allocation and motion planning. The goal is to combine a predefined set of objects to form something new while considering task execution with the…

Robotics · Computer Science 2022-08-03 Niklas Funk , Svenja Menzenbach , Georgia Chalvatzaki , Jan Peters

In the past few years, a lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs). In the most recent works, differentiable…

Computer Vision and Pattern Recognition · Computer Science 2020-09-09 Baris Gecer , Stylianos Ploumpis , Irene Kotsia , Stefanos Zafeiriou

Recently, 3D Gaussian Splatting (3DGS) has demonstrated remarkable success in 3D reconstruction and novel view synthesis. However, reconstructing 3D scenes from sparse viewpoints remains highly challenging due to insufficient visual…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Zhaorui Wang , Yi Gu , Deming Zhou , Renjing Xu

The low-quality structure in raw depth maps is prevalent in real-world RGB-D datasets, which makes real-world depth recovery a critical task in recent years. However, the lack of paired raw-ground truth (raw-GT) data in the real world poses…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Delong Suzhang , Meng Yang

The generation of high-fidelity view synthesis is essential for robotic navigation and interaction but remains challenging, particularly in indoor environments and real-time scenarios. Existing techniques often require significant…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Sen Wang , Qing Cheng , Stefano Gasperini , Wei Zhang , Shun-Cheng Wu , Niclas Zeller , Daniel Cremers , Nassir Navab

Recent neural rendering and reconstruction techniques, such as NeRFs or Gaussian Splatting, have shown remarkable novel view synthesis capabilities but require hundreds of images of the scene from diverse viewpoints to render high-quality…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Felix Tristram , Stefano Gasperini , Nassir Navab , Federico Tombari

This paper presents RoGSplat, a novel approach for synthesizing high-fidelity novel views of unseen human from sparse multi-view images, while requiring no cumbersome per-subject optimization. Unlike previous methods that typically struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Junjin Xiao , Qing Zhang , Yonewei Nie , Lei Zhu , Wei-Shi Zheng

We explore the task of geometric reconstruction of images captured from a mixture of ground and aerial views. Current state-of-the-art learning-based approaches fail to handle the extreme viewpoint variation between aerial-ground image…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Khiem Vuong , Anurag Ghosh , Deva Ramanan , Srinivasa Narasimhan , Shubham Tulsiani

In recent years, advanced image editing and generation methods have rapidly evolved, making detecting and locating forged image content increasingly challenging. Most existing image forgery detection methods rely on identifying the edited…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Hengrun Zhao , Yunzhi Zhuge , Yifan Wang , Lijun Wang , Huchuan Lu , Yu Zeng

General scene understanding for robotics requires flexible semantic representation, so that novel objects and structures which may not have been known at training time can be identified, segmented and grouped. We present an algorithm which…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 Kirill Mazur , Edgar Sucar , Andrew J. Davison

Neural Radiance Fields (NeRF) achieve photo-realistic view synthesis with densely captured input images. However, the geometry of NeRF is extremely under-constrained given sparse views, resulting in significant degradation of novel view…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Zheng Chen , Chen Wang , Yuan-Chen Guo , Song-Hai Zhang
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