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Related papers: Event-based Stereo Depth Estimation: A Survey

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Recent video depth estimation methods achieve great performance by following the paradigm of image depth estimation, i.e., typically fine-tuning pre-trained video diffusion models with massive data. However, we argue that video depth…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Haodong Li , Chen Wang , Jiahui Lei , Kostas Daniilidis , Lingjie Liu

The bioinspired event camera, distinguished by its exceptional temporal resolution, high dynamic range, and low power consumption, has been extensively studied in recent years for motion estimation, robotic perception, and object detection.…

Robotics · Computer Science 2025-07-23 Shuolong Chen , Xingxing Li , Liu Yuan

Endoscopic depth estimation is a critical technology for improving the safety and precision of minimally invasive surgery. It has attracted considerable attention from researchers in medical imaging, computer vision, and robotics. Over the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Ke Niu , Zeyun Liu , Xue Feng , Heng Li , Qika Lin , Kaize Shi

Event cameras, often referred to as dynamic vision sensors, are groundbreaking sensors capable of capturing changes in light intensity asynchronously, offering exceptional temporal resolution and energy efficiency. These attributes make…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Mira Adra , Simone Melcarne , Nelida Mirabet-Herranz , Jean-Luc Dugelay

Event cameras are bio-inspired sensors that perform well in challenging illumination conditions and have high temporal resolution. However, their concept is fundamentally different from traditional frame-based cameras. The pixels of an…

Computer Vision and Pattern Recognition · Computer Science 2022-06-13 Xin Peng , Ling Gao , Yifu Wang , Laurent Kneip

Scene depth estimation from stereo and monocular imagery is critical for extracting 3D information for downstream tasks such as scene understanding. Recently, learning-based methods for depth estimation have received much attention due to…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Zhaoshuo Li , Nathan Drenkow , Hao Ding , Andy S. Ding , Alexander Lu , Francis X. Creighton , Russell H. Taylor , Mathias Unberath

Event-based vision, inspired by the human visual system, offers transformative capabilities such as low latency, high dynamic range, and reduced power consumption. This paper presents a comprehensive survey of event cameras, tracing their…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Bharatesh Chakravarthi , Aayush Atul Verma , Kostas Daniilidis , Cornelia Fermuller , Yezhou Yang

Event camera is a new type of sensor that is different from traditional cameras. Each pixel is triggered asynchronously by an event. The trigger event is the change of the brightness irradiated on the pixel. If the increment or decrement is…

Computer Vision and Pattern Recognition · Computer Science 2022-03-28 Kun Xiao , Pengju Li , Guohui Wang , Zhi Li , Yi Chen , Yongfeng Xie , Yuqiang Fang

Despite the dynamic development of computer vision algorithms, the implementation of perception and control systems for autonomous vehicles such as drones and self-driving cars still poses many challenges. A video stream captured by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Piotr Wzorek , Tomasz Kryjak

Event cameras are bio-inspired vision sensors which measure per pixel brightness changes. They offer numerous benefits over traditional, frame-based cameras, including low latency, high dynamic range, high temporal resolution and low power…

Computer Vision and Pattern Recognition · Computer Science 2021-08-18 Simon Klenk , Jason Chui , Nikolaus Demmel , Daniel Cremers

Event cameras, with their high dynamic range (HDR) and low latency, offer a promising alternative for robust depth estimation in challenging environments. However, many event-based depth estimation approaches are constrained by small-scale…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Sadiq Layi Macaulay , Nimet Kaygusuz , Simon Hadfield

Video depth estimation is crucial in various applications, such as scene reconstruction and augmented reality. In contrast to the naive method of estimating depths from images, a more sophisticated approach uses temporal information,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Elena Kosheleva , Sunil Jaiswal , Faranak Shamsafar , Noshaba Cheema , Klaus Illgner-Fehns , Philipp Slusallek

Event cameras offer multiple advantages in monocular egocentric 3D human pose estimation from head-mounted devices, such as millisecond temporal resolution, high dynamic range, and negligible motion blur. Existing methods effectively…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Mayur Deshmukh , Hiroyasu Akada , Helge Rhodin , Christian Theobalt , Vladislav Golyanik

Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The resulting streams of events are of high value by themselves, especially for high speed…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 F. Paredes-Vallés , G. C. H. E. de Croon

Depth completion in dynamic scenes poses significant challenges due to rapid ego-motion and object motion, which can severely degrade the quality of input modalities such as RGB images and LiDAR measurements. Conventional RGB-D sensors…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Zhiqiang Yan , Jianhao Jiao , Zhengxue Wang , Gim Hee Lee

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , Kuk-Jin Yoon

Depth sensing is crucial for 3D reconstruction and scene understanding. Active depth sensors provide dense metric measurements, but often suffer from limitations such as restricted operating ranges, low spatial resolution, sensor…

Computer Vision and Pattern Recognition · Computer Science 2019-01-10 Chao Liu , Jinwei Gu , Kihwan Kim , Srinivasa Narasimhan , Jan Kautz

Depth sensing is an important problem for 3D vision-based robotics. Yet, a real-world active stereo or ToF depth camera often produces noisy and incomplete depth which bottlenecks robot performances. In this work, we propose D3RoMa, a…

We present a novel method to estimate the surface normal of an object in an ambient light environment using RGB and event cameras. Modern photometric stereo methods rely on an RGB camera, mainly in a dark room, to avoid ambient…

Computer Vision and Pattern Recognition · Computer Science 2023-08-11 Wonjeong Ryoo , Giljoo Nam , Jae-Sang Hyun , Sangpil Kim

Event cameras offering high dynamic range and low latency have emerged as disruptive technologies in imaging. Despite growing research on leveraging these benefits for different imaging tasks, a comprehensive study of recently advances and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Yunfan Lu , Xiaogang Xu , Pengteng Li , Yusheng Wang , Yi Cui , Huizai Yao , Hui Xiong