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2D cameras are often used in interactive systems. Other systems like gaming consoles provide more powerful 3D cameras for short range depth sensing. Overall, these cameras are not reliable in large, complex environments. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Mohamed Benkedadra , Matei Mancas , Sidi Ahmed Mahmoudi

Despite the substantial progress in deep learning, its adoption in industrial robotics projects remains limited, primarily due to challenges in data acquisition and labeling. Previous sim2real approaches using domain randomization require…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Kaixin Bai , Lei Zhang , Zhaopeng Chen , Fang Wan , Jianwei Zhang

Gradient-based algorithms are crucial to modern computer-vision and graphics applications, enabling learning-based optimization and inverse problems. For example, photorealistic differentiable rendering pipelines for color images have been…

Computer Vision and Pattern Recognition · Computer Science 2021-08-10 Benjamin Planche , Rajat Vikram Singh

Traditional depth sensors generate accurate real world depth estimates that surpass even the most advanced learning approaches trained only on simulation domains. Since ground truth depth is readily available in the simulation domain but…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Isabella Liu , Edward Yang , Jianyu Tao , Rui Chen , Xiaoshuai Zhang , Qing Ran , Zhu Liu , Hao Su

In robotic vision, a de-facto paradigm is to learn in simulated environments and then transfer to real-world applications, which poses an essential challenge in bridging the sim-to-real domain gap. While mainstream works tackle this problem…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Xingyu Liu , Chenyangguang Zhang , Gu Wang , Ruida Zhang , Xiangyang Ji

Active stereo systems are used in many robotic applications that require 3D information. These depth sensors, however, suffer from stereo artefacts and do not provide dense depth estimates.In this work, we present the first self-supervised…

Computer Vision and Pattern Recognition · Computer Science 2022-01-21 Frederik Warburg , Daniel Hernandez-Juarez , Juan Tarrio , Alexander Vakhitov , Ujwal Bonde , Pablo F. Alcantarilla

Building home assistant robots has long been a pursuit for vision and robotics researchers. To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real…

Computer Vision and Pattern Recognition · Computer Science 2020-03-20 Fanbo Xiang , Yuzhe Qin , Kaichun Mo , Yikuan Xia , Hao Zhu , Fangchen Liu , Minghua Liu , Hanxiao Jiang , Yifu Yuan , He Wang , Li Yi , Angel X. Chang , Leonidas J. Guibas , Hao Su

Estimating depth from RGB images is a long-standing ill-posed problem, which has been explored for decades by the computer vision, graphics, and machine learning communities. Among the existing techniques, stereo matching remains one of the…

Computer Vision and Pattern Recognition · Computer Science 2021-01-26 Hamid Laga , Laurent Valentin Jospin , Farid Boussaid , Mohammed Bennamoun

This paper presents a novel general-purpose guided stereo paradigm that mimics the active stereo principle by replacing the unreliable physical pattern projector with a depth sensor. It works by projecting virtual patterns consistent with…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Luca Bartolomei , Matteo Poggi , Fabio Tosi , Andrea Conti , Stefano Mattoccia

Many studies utilize dual-pixel (DP) sensor phase characteristics for various applications, such as depth estimation and deblurring. However, since the DP image features are entirely determined by the camera hardware, DP-depth paired…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Fengchen He , Dayang Zhao , Hao Xu , Tingwei Quan , Shaoqun Zeng

Collimator detection remains a challenging task in X-ray systems with unreliable or non-available information about the detectors position relative to the source. This paper presents a physically motivated image processing pipeline for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Benjamin El-Zein , Dominik Eckert , Thomas Weber , Maximilian Rohleder , Ludwig Ritschl , Steffen Kappler , Andreas Maier

The stereo-matching problem, i.e., matching corresponding features in two different views to reconstruct depth, is efficiently solved in biology. Yet, it remains the computational bottleneck for classical machine vision approaches. By…

Computer Vision and Pattern Recognition · Computer Science 2021-04-07 Nicoletta Risi , Enrico Calabrese , Giacomo Indiveri

State-of-the-art supervised stereo matching methods have achieved remarkable performance on various benchmarks. However, their generalization to real-world scenarios remains challenging due to the scarcity of annotated real-world stereo…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Xianqi Wang , Hao Yang , Gangwei Xu , Junda Cheng , Min Lin , Yong Deng , Jinliang Zang , Yurui Chen , Xin Yang

Traditional ultrasound simulators solve the wave equation to model pressure distribution fields, achieving high accuracy but requiring significant computational time and resources. To address this, ray tracing approaches have been…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Felix Duelmer , Mohammad Farid Azampour , Magdalena Wysocki , Nassir Navab

Constructing simulation scenes that are both visually and physically realistic is a problem of practical interest in domains ranging from robotics to computer vision. This problem has become even more relevant as researchers wielding large…

Developing embodied agents in simulation has been a key research topic in recent years. Exciting new tasks, algorithms, and benchmarks have been developed in various simulators. However, most of them assume deaf agents in silent…

Robotics · Computer Science 2023-09-19 Ruohan Gao , Hao Li , Gokul Dharan , Zhuzhu Wang , Chengshu Li , Fei Xia , Silvio Savarese , Li Fei-Fei , Jiajun Wu

Depth estimation is an important computer vision task, useful in particular for navigation in autonomous vehicles, or for object manipulation in robotics. Here we solved it using an end-to-end neuromorphic approach, combining two…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Ulysse Rançon , Javier Cuadrado-Anibarro , Benoit R. Cottereau , Timothée Masquelier

This paper is focused on delivering a solution that can scan and reconstruct the 3D profile of a pipeline in real-time using a crawler robot. A structured infrared (IR) laser ring projector and a stereo camera system are used to generate…

Robotics · Computer Science 2019-07-30 Amal Gunatilake , Lasitha Piyathilaka , Sarath Kodagoda , Stephen Barclay , Dammika Vitanage

Transparent object depth perception poses a challenge in everyday life and logistics, primarily due to the inability of standard 3D sensors to accurately capture depth on transparent or reflective surfaces. This limitation significantly…

Robotics · Computer Science 2026-03-10 Kaixin Bai , Huajian Zeng , Lei Zhang , Yiwen Liu , Hongli Xu , Zhaopeng Chen , Jianwei Zhang

Robotic surgery has become a powerful tool for performing minimally invasive procedures, providing advantages in dexterity, precision, and 3D vision, over traditional surgery. One popular robotic system is the da Vinci surgical platform,…

Computer Vision and Pattern Recognition · Computer Science 2017-05-24 Menglong Ye , Edward Johns , Ankur Handa , Lin Zhang , Philip Pratt , Guang-Zhong Yang
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