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Restoring clear frames from rainy videos presents a significant challenge due to the rapid motion of rain streaks. Traditional frame-based visual sensors, which capture scene content synchronously, struggle to capture the fast-moving…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Hanwen Liang , Xian Zhong , Wenxuan Liu , Yajing Zheng , Wenxin Huang , Zhaofei Yu , Tiejun Huang

Text-to-video generation is expensive, so only a few samples are typically produced per prompt. In this low-sample regime, maximizing the value of each batch requires high cross-video diversity. Recent methods improve diversity for image…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Xinshuang Liu , Runfa Blark Li , Truong Nguyen

Contemporary approaches frame the color constancy problem as learning camera specific illuminant mappings. While high accuracy can be achieved on camera specific data, these models depend on camera spectral sensitivity and typically exhibit…

Computer Vision and Pattern Recognition · Computer Science 2020-03-03 Daniel Hernandez-Juarez , Sarah Parisot , Benjamin Busam , Ales Leonardis , Gregory Slabaugh , Steven McDonagh

Combining the Color and Event cameras (also called Dynamic Vision Sensors, DVS) for robust object tracking is a newly emerging research topic in recent years. Existing color-event tracking framework usually contains multiple scattered…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Chuanming Tang , Xiao Wang , Ju Huang , Bo Jiang , Lin Zhu , Jianlin Zhang , Yaowei Wang , Yonghong Tian

Event cameras offer significant advantages, including a wide dynamic range, high temporal resolution, and immunity to motion blur, making them highly promising for addressing challenging visual conditions. Extracting and utilizing effective…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Xin Dong , Yiwei Zhang , Yangjie Cui , Jinwu Xiang , Daochun Li , Zhan Tu

Recording fast motion in a high FPS (frame-per-second) requires expensive high-speed cameras. As an alternative, interpolating low-FPS videos from commodity cameras has attracted significant attention. If only low-FPS videos are available,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Weihua He , Kaichao You , Zhendong Qiao , Xu Jia , Ziyang Zhang , Wenhui Wang , Huchuan Lu , Yaoyuan Wang , Jianxing Liao

Event cameras are bio-inspired sensors that offer advantages over traditional cameras. They operate asynchronously, sampling the scene at microsecond resolution and producing a stream of brightness changes. This unconventional output has…

Computer Vision and Pattern Recognition · Computer Science 2022-09-14 Suman Ghosh , Guillermo Gallego

Different from traditional video cameras, event cameras capture asynchronous events stream in which each event encodes pixel location, trigger time, and the polarity of the brightness changes. In this paper, we introduce a novel graph-based…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Yijin Li , Han Zhou , Bangbang Yang , Ye Zhang , Zhaopeng Cui , Hujun Bao , Guofeng Zhang

Event-based keypoint detection and matching holds significant potential, enabling the integration of event sensors into highly optimized Visual SLAM systems developed for frame cameras over decades of research. Unfortunately, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Yannick Burkhardt , Simon Schaefer , Stefan Leutenegger

Event cameras offer high temporal resolution and power efficiency, making them well-suited for edge AI applications. However, their high event rates present challenges for data transmission and processing. Subsampling methods provide a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Hesam Araghi , Jan van Gemert , Nergis Tomen

We address the challenging problem of dense dynamic scene reconstruction and camera pose estimation from multiple freely moving cameras -- a setting that arises naturally when multiple observers capture a shared event. Prior approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Shuo Sun , Unal Artan , Malcolm Mielle , Achim J. Lilienthaland , Martin Magnusson

Event-based cameras are bio-inspired novel sensors that asynchronously record changes in illumination in the form of events, thus resulting in significant advantages over conventional cameras in terms of low power utilization, high dynamic…

Machine Learning · Statistics 2020-02-18 Lakshmi Annamalai , Anirban Chakraborty , Chetan Singh Thakur

3D hand tracking methods based on monocular RGB videos are easily affected by motion blur, while event camera, a sensor with high temporal resolution and dynamic range, is naturally suitable for this task with sparse output and low power…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Chuanlin Lan , Ziyuan Yin , Arindam Basu , Rosa H. M. Chan

Extreme image or video completion, where, for instance, we only retain 1% of pixels in random locations, allows for very cheap sampling in terms of the required pre-processing. The consequence is, however, a reconstruction that is…

Computer Vision and Pattern Recognition · Computer Science 2020-04-15 Majed El Helou , Ruofan Zhou , Frank Schmutz , Fabrice Guibert , Sabine Süsstrunk

We present a method for estimating dense continuous-time optical flow from event data. Traditional dense optical flow methods compute the pixel displacement between two images. Due to missing information, these approaches cannot recover the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Mathias Gehrig , Manasi Muglikar , Davide Scaramuzza

Accurate depth estimation under adverse night conditions has practical impact and applications, such as on autonomous driving and rescue robots. In this work, we studied monocular depth estimation at night time in which various adverse…

Computer Vision and Pattern Recognition · Computer Science 2023-02-09 Peilun Shi , Jiachuan Peng , Jianing Qiu , Xinwei Ju , Frank Po Wen Lo , Benny Lo

Event cameras operate fundamentally differently from traditional Active Pixel Sensor (APS) cameras, offering significant advantages. Recent research has developed simulators to convert video frames into events, addressing the shortage of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Xiao Jiang , Fei Zhou , Jiongzhi Lin

Although recent text-to-video generative models are getting more capable of following external camera controls, imposed by either text descriptions or camera trajectories, they still struggle to generalize to unconventional camera motions,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Qiucheng Wu , Handong Zhao , Zhixin Shu , Jing Shi , Yang Zhang , Shiyu Chang

Event cameras are a new type of brain-inspired visual sensor with advantages such as high dynamic range and high temporal resolution. The geometric calibration of event cameras, which involves determining their intrinsic and extrinsic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Zibin Liu , Shunkun Liang , Banglei Guan , Dongcai Tan , Yang Shang , Qifeng Yu

In low-light environments, conventional cameras often struggle to capture clear multi-view images of objects due to dynamic range limitations and motion blur caused by long exposure. Event cameras, with their high-dynamic range and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Jingqian Wu , Peiqi Duan , Zongqiang Wang , Changwei Wang , Boxin Shi , Edmund Y. Lam
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