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Related papers: Event-Driven Dynamic Scene Depth Completion

200 papers

Detecting and magnifying imperceptible high-frequency motions in real-world scenarios has substantial implications for industrial and medical applications. These motions are characterized by small amplitudes and high frequencies.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Yutian Chen , Shi Guo , Fangzheng Yu , Feng Zhang , Jinwei Gu , Tianfan Xue

Event cameras such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such as optical flow estimation. Most of the existing optical…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Zhexiong Wan , Yuchao Dai , Yuxin Mao

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 encode visual information with high temporal precision, low data-rate, and high-dynamic range. Thanks to these characteristics, event cameras are particularly suited for scenarios with high motion, challenging lighting…

Computer Vision and Pattern Recognition · Computer Science 2020-12-10 Etienne Perot , Pierre de Tournemire , Davide Nitti , Jonathan Masci , Amos Sironi

Event camera sensors are bio-inspired sensors which asynchronously capture per-pixel brightness changes and output a stream of events encoding the polarity, location and time of these changes. These systems are witnessing rapid advancements…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Aupendu Kar , Vishnu Raj , Guan-Ming Su

Event cameras are bio-inspired sensors with some notable features, including high dynamic range and low latency, which makes them exceptionally suitable for perception in challenging scenarios such as high-speed motion and extreme lighting…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Kuangyi Chen , Jun Zhang , Friedrich Fraundorfer

Dynamic Vision Sensors (DVS) capture event data with high temporal resolution and low power consumption, presenting a more efficient solution for visual processing in dynamic and real-time scenarios compared to conventional video capture…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Yiting Dong , Xiang He , Guobin Shen , Dongcheng Zhao , Yang Li , Yi Zeng

Depth completion involves estimating a dense depth image from sparse depth measurements, often guided by a color image. While linear upsampling is straight forward, it results in artifacts including depth pixels being interpolated in empty…

Computer Vision and Pattern Recognition · Computer Science 2019-03-14 Saif Imran , Yunfei Long , Xiaoming Liu , Daniel Morris

Event-based cameras (ECs) have emerged as bio-inspired sensors that report pixel brightness changes asynchronously, offering unmatched speed and efficiency in vision sensing. Despite their high dynamic range, temporal resolution, low power…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Seyed Ehsan Marjani Bajestani , Giovanni Beltrame

Event cameras can record scene dynamics with high temporal resolution, providing rich scene details for monocular depth estimation (MDE) even at low-level illumination. Therefore, existing complementary learning approaches for MDE fuse…

Computer Vision and Pattern Recognition · Computer Science 2024-03-01 Haotian Liu , Sanqing Qu , Fan Lu , Zongtao Bu , Florian Roehrbein , Alois Knoll , Guang Chen

Visual Deformation Measurement (VDM) aims to recover dense deformation fields by tracking surface motion from camera observations. Traditional image-based methods rely on minimal inter-frame motion to constrain the correspondence search…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Yuliang Wu , Wei Zhai , Yuxin Cui , Tiesong Zhao , Yang Cao , Zheng-Jun Zha

With the rapid development of deep learning, video deraining has experienced significant progress. However, existing video deraining pipelines cannot achieve satisfying performance for scenes with rain layers of complex spatio-temporal…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Yueyi Zhang , Jin Wang , Wenming Weng , Xiaoyan Sun , Zhiwei Xiong

Event-based cameras are bio-inspired vision sensors whose pixels work independently from each other and respond asynchronously to brightness changes, with microsecond resolution. Their advantages make it possible to tackle challenging…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Yi Zhou , Guillermo Gallego , Shaojie Shen

Event cameras have higher temporal resolution, and require less storage and bandwidth compared to traditional RGB cameras. However, due to relatively lagging performance of event-based approaches, event cameras have not yet replace…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Muhammad Ahmed Ullah Khan , Abdul Hannan Khan , Andreas Dengel

Depth information is useful for many applications. Active depth sensors are appealing because they obtain dense and accurate depth maps. However, due to issues that range from power constraints to multi-sensor interference, these sensors…

Image and Video Processing · Electrical Eng. & Systems 2020-02-04 James Noraky , Vivienne Sze

Robust depth estimation under dynamic and adverse lighting conditions is essential for robotic systems. Currently, depth foundation models, such as Depth Anything, achieve great success in ideal scenes but remain challenging under adverse…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Shihan Peng , Yuyang Xiong , Hanyu Zhou , Zhiwei Shi , Haoyue Liu , Gang Chen , Luxin Yan , Yi Chang

Event cameras offer significant advantages for low-light video enhancement, primarily due to their high dynamic range. Current research, however, is severely limited by the absence of large-scale, real-world, and spatio-temporally aligned…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Kanghao Chen , Guoqiang Liang , Hangyu Li , Yunfan Lu , Lin Wang

Non-uniform image deblurring is a challenging task due to the lack of temporal and textural information in the blurry image itself. Complementary information from auxiliary sensors such event sensors are being explored to address these…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Patricia Vitoria , Stamatios Georgoulis , Stepan Tulyakov , Alfredo Bochicchio , Julius Erbach , Yuanyou Li

Event cameras are bio-inspired, motion-activated sensors that demonstrate substantial potential in handling challenging situations, such as motion blur and high-dynamic range. In this paper, we proposed EVI-SAM to tackle the problem of 6…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Weipeng Guan , Peiyu Chen , Huibin Zhao , Yu Wang , Peng Lu

Dynamic Vision Sensor (DVS) can asynchronously output the events reflecting apparent motion of objects with microsecond resolution, and shows great application potential in monitoring and other fields. However, the output event stream of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Jinze Chen , Yang Wang , Yang Cao , Feng Wu , Zheng-Jun Zha