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Accurate moving object segmentation is an essential task for autonomous driving. It can provide effective information for many downstream tasks, such as collision avoidance, path planning, and static map construction. How to effectively…

Computer Vision and Pattern Recognition · Computer Science 2022-07-06 Jiadai Sun , Yuchao Dai , Xianjing Zhang , Jintao Xu , Rui Ai , Weihao Gu , Xieyuanli Chen

In-camera light scattering is a typical form of non-systematic interference in indirect Time-of-Flight (iToF) cameras, primarily caused by multiple reflections and optical path variations within the camera body. This effect can…

Optics · Physics 2025-11-05 Yansong Du , Jingtong Yao , Yuting Zhou , Feiyu Jiao , Zhaoxiang Jiang , Xun Guan

We investigate methods for determining if a planar surface contains geometric deviations (e.g., protrusions, objects, divots, or cliffs) using only an instantaneous measurement from a miniature optical time-of-flight sensor. The key to our…

Robotics · Computer Science 2024-08-08 Carter Sifferman , William Sun , Mohit Gupta , Michael Gleicher

Detecting objects such as cars and pedestrians in 3D plays an indispensable role in autonomous driving. Existing approaches largely rely on expensive LiDAR sensors for accurate depth information. While recently pseudo-LiDAR has been…

Computer Vision and Pattern Recognition · Computer Science 2020-02-18 Yurong You , Yan Wang , Wei-Lun Chao , Divyansh Garg , Geoff Pleiss , Bharath Hariharan , Mark Campbell , Kilian Q. Weinberger

We propose a new approach called LiDAR-Flow to robustly estimate a dense scene flow by fusing a sparse LiDAR with stereo images. We take the advantage of the high accuracy of LiDAR to resolve the lack of information in some regions of…

Computer Vision and Pattern Recognition · Computer Science 2019-12-16 Ramy Battrawy , René Schuster , Oliver Wasenmüller , Qing Rao , Didier Stricker

High frame rate and accurate depth estimation plays an important role in several tasks crucial to robotics and automotive perception. To date, this can be achieved through ToF and LiDAR devices for indoor and outdoor applications,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Andrea Conti , Matteo Poggi , Valerio Cambareri , Stefano Mattoccia

Lidar point cloud distortion from moving object is an important problem in autonomous driving, and recently becomes even more demanding with the emerging of newer lidars, which feature back-and-forth scanning patterns. Accurately estimating…

Robotics · Computer Science 2022-07-05 Wen Yang , Zheng Gong , Baifu Huang , Xiaoping Hong

Existing LiDAR 3D object detection methods predominantely rely on sparse convolutions and/or transformers, which can be challenging to run on resource-constrained edge devices, due to irregular memory access patterns and high computational…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Shizhong Han , Hsin-Pai Cheng , Hong Cai , Jihad Masri , Soyeb Nagori , Fatih Porikli

Enhancing visual odometry by exploiting sparse depth measurements from LiDAR is a promising solution for improving tracking accuracy of an odometry. Most existing works utilize a monocular pinhole camera, yet could suffer from poor…

Robotics · Computer Science 2025-09-16 Qirui Hu , Zikang Yuan , Tianle Xu , Xiaoxiang Wang , Jinni Geng , Xin Yang

Lidar sensors are widely used in various applications, ranging from scientific fields over industrial use to integration in consumer products. With an ever growing number of different driver assistance systems, they have been introduced to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-09 Frederik Hasecke , Lukas Hahn , Anton Kummert

Active imaging systems sample the Transient Light Transport Matrix (TLTM) for a scene by sequentially illuminating various positions in this scene using a controllable light source, and then measuring the resulting spatiotemporal light…

As the perception range of LiDAR increases, LiDAR-based 3D object detection becomes a dominant task in the long-range perception task of autonomous driving. The mainstream 3D object detectors usually build dense feature maps in the network…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Lue Fan , Feng Wang , Naiyan Wang , Zhaoxiang Zhang

Single-Photon Light Detection and Ranging (SP-LiDAR is emerging as a leading technology for long-range, high-precision 3D vision tasks. In SP-LiDAR, timestamps encode two complementary pieces of information: pulse travel time (depth) and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Hashan K. Weerasooriya , Prateek Chennuri , Weijian Zhang , Istvan Gyongy , Stanley H. Chan

Fourier ptychographic (FP) microscope is a coherent imaging method that can synthesize an image with a higher bandwidth using multiple low-bandwidth images captured at different spatial frequency regions. The method's demand for multiple…

Optics · Physics 2016-03-25 Jaebum Chung , Hangwen Lu , Xiaoze Ou , Haojiang Zhou , Changhuei Yang

We present a method to reconstruct dynamic scenes from monocular continuous-wave time-of-flight (C-ToF) cameras using raw sensor samples that achieves similar or better accuracy than neural volumetric approaches and is 100x faster. Quickly…

For active optical imaging, the use of single-photon detectors can greatly improve the detection sensitivity of the system. However, the traditional maximum-likelihood based imaging method needs a long acquisition time to capture clear…

Rapid and programmable shaping of light fields is central to modern microscopy, display technologies, optical communications and sensing, quantum engineering, and quantum information processing. Current wavefront shaping technologies face a…

Quantum Physics · Physics 2026-01-15 Xin Wei , Zeyang Li , Abhishek V. Karve , Adam L. Shaw , David I. Schuster , Jonathan Simon

To realize low-latency spatial transmission system for immersive telepresence, there are two major problems: capturing dynamic 3D scene densely and processing them in real time. LiDAR sensors capture 3D in real time, but produce sparce…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Kazuhiko Murasaki , Shunsuke Konagai , Masakatsu Aoki , Taiga Yoshida , Ryuichi Tanida

Lidars and cameras are critical sensors that provide complementary information for 3D detection in autonomous driving. While most prevalent methods progressively downscale the 3D point clouds and camera images and then fuse the high-level…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Zixuan Yin , Han Sun , Ningzhong Liu , Huiyu Zhou , Jiaquan Shen

Safety of the Intended Functionality (SOTIF) addresses sensor performance limitations and deep learning-based object detection insufficiencies to ensure the intended functionality of Automated Driving Systems (ADS). This paper presents a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Milin Patel , Rolf Jung