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Slow shutter speed and long exposure time of frame-based cameras often cause visual blur and loss of inter-frame information, degenerating the overall quality of captured videos. To this end, we present a unified framework of event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Xiang Zhang , Lei Yu

Exposure-agnostic video frame interpolation (VFI) is a challenging task that aims to recover sharp, high-frame-rate videos from blurry, low-frame-rate inputs captured under unknown and dynamic exposure conditions. Event cameras are sensors…

Image and Video Processing · Electrical Eng. & Systems 2025-10-28 Junsik Jung , Yoonki Cho , Woo Jae Kim , Lin Wang , Sune-eui Yoon

Video Frame Interpolation aims to recover realistic missing frames between observed frames, generating a high-frame-rate video from a low-frame-rate video. However, without additional guidance, the large motion between frames makes this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Jingxi Chen , Brandon Y. Feng , Haoming Cai , Tianfu Wang , Levi Burner , Dehao Yuan , Cornelia Fermuller , Christopher A. Metzler , Yiannis Aloimonos

Achieving sharp 3D reconstruction from motion-blurred images alone becomes challenging, motivating recent methods to incorporate event cameras, benefiting from microsecond temporal resolution. However, they suffer from residual artifacts…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Feiyu An , Yufei Deng , Zihui Zhang , Rong Xiao

In low-light conditions, capturing videos with frame-based cameras often requires long exposure times, resulting in motion blur and reduced visibility. While frame-based motion deblurring and low-light enhancement have been studied, they…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Taewoo Kim , Jaeseok Jeong , Hoonhee Cho , Yuhwan Jeong , Kuk-Jin Yoon

Event-based cameras measure intensity changes (called `events') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the `active pixel sensor' (APS), the `Dynamic and Active-pixel Vision Sensor'…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Liyuan Pan , Richard Hartley , Cedric Scheerlinck , Miaomiao Liu , Xin Yu , Yuchao Dai

High dynamic range imaging (HDRI) for real-world dynamic scenes is challenging because moving objects may lead to hybrid degradation of low dynamic range and motion blur. Existing event-based approaches only focus on a separate task, while…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Li Xiaopeng , Zeng Zhaoyuan , Fan Cien , Zhao Chen , Deng Lei , Yu Lei

Effective video frame interpolation hinges on the adept handling of motion in the input scene. Prior work acknowledges asynchronous event information for this, but often overlooks whether motion induces blur in the video, limiting its scope…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Lei Sun , Daniel Gehrig , Christos Sakaridis , Mathias Gehrig , Jingyun Liang , Peng Sun , Zhijie Xu , Kaiwei Wang , Luc Van Gool , Davide Scaramuzza

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

Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process. For event-based cameras, however, fast motion can be captured as events at high time…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Zhe Jiang , Yu Zhang , Dongqing Zou , Jimmy Ren , Jiancheng Lv , Yebin Liu

Video Frame Interpolation (VFI) is a fundamental yet challenging task in computer vision, particularly under conditions involving large motion, occlusion, and lighting variation. Recent advancements in event cameras have opened up new…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Hanle Zheng , Xujie Han , Zegang Peng , Shangbin Zhang , Guangxun Du , Zhuo Zou , Xilin Wang , Jibin Wu , Hao Guo , Lei Deng

In this paper, we tackle the task of blurry video super-resolution (BVSR), aiming to generate high-resolution (HR) videos from low-resolution (LR) and blurry inputs. Current BVSR methods often fail to restore sharp details at high…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dachun Kai , Yueyi Zhang , Jin Wang , Zeyu Xiao , Zhiwei Xiong , Xiaoyan Sun

Traditional frame-based cameras inevitably suffer from motion blur due to long exposure times. As a kind of bio-inspired camera, the event camera records the intensity changes in an asynchronous way with high temporal resolution, providing…

Computer Vision and Pattern Recognition · Computer Science 2023-01-13 Lei Sun , Christos Sakaridis , Jingyun Liang , Qi Jiang , Kailun Yang , Peng Sun , Yaozu Ye , Kaiwei Wang , Luc Van Gool

Video deblurring is a challenging task that aims to recover sharp sequences from blur and noisy observations. The image-formation model plays a crucial role in traditional model-based methods, constraining the possible solutions. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Zhihao Huang , Santiago Lopez-Tapia , Aggelos K. Katsaggelos

Event-based cameras can measure intensity changes (called `{\it events}') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the active pixel sensor (APS), the event camera allows simultaneous output…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Liyuan Pan , Cedric Scheerlinck , Xin Yu , Richard Hartley , Miaomiao Liu , Yuchao Dai

Natural videos captured by consumer cameras often suffer from low framerate and motion blur due to the combination of dynamic scene complexity, lens and sensor imperfection, and less than ideal exposure setting. As a result, computational…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Wei Shang , Dongwei Ren , Yi Yang , Hongzhi Zhang , Kede Ma , Wangmeng Zuo

Motion deblurring is a highly ill-posed problem due to the loss of motion information in the blur degradation process. Since event cameras can capture apparent motion with a high temporal resolution, several attempts have explored the…

Computer Vision and Pattern Recognition · Computer Science 2022-07-27 Taewoo Kim , Jeongmin Lee , Lin Wang , Kuk-Jin Yoon

Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes. However, developing algorithms for event measurements requires a new class…

Computer Vision and Pattern Recognition · Computer Science 2018-08-14 Alex Zihao Zhu , Liangzhe Yuan , Kenneth Chaney , Kostas Daniilidis

Video frame interpolation, the process of synthesizing intermediate frames between sequential video frames, has made remarkable progress with the use of event cameras. These sensors, with microsecond-level temporal resolution, fill…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Yuhan Liu , Yongjian Deng , Hao Chen , Bochen Xie , Youfu Li , Zhen Yang

Blind video deblurring restores sharp frames from a blurry sequence without any prior. It is a challenging task because the blur due to camera shake, object movement and defocusing is heterogeneous in both temporal and spatial dimensions.…

Computer Vision and Pattern Recognition · Computer Science 2019-12-10 Junru Wu , Xiang Yu , Ding Liu , Manmohan Chandraker , Zhangyang Wang
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