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Related papers: TimeLens: Event-based Video Frame Interpolation

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Flow-based frame interpolation methods ensure motion stability through estimated intermediate flow but often introduce severe artifacts in complex motion regions. Recent generative approaches, boosted by large-scale pre-trained video…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Guozhen Zhang , Yuhan Zhu , Yutao Cui , Xiaotong Zhao , Kai Ma , Limin Wang

Compared to regular cameras, Dynamic Vision Sensors or Event Cameras can output compact visual data based on a change in the intensity in each pixel location asynchronously. In this paper, we study the application of current image-based…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Masoud Dayani Najafabadi , Mohammad Reza Ahmadzadeh

We introduce a method for using event camera data in novel view synthesis via Gaussian Splatting. Event cameras offer exceptional temporal resolution and a high dynamic range. Leveraging these capabilities allows us to effectively address…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Toshiya Yura , Ashkan Mirzaei , Igor Gilitschenski

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

Current optical flow methods exploit the stable appearance of frame (or RGB) data to establish robust correspondences across time. Event cameras, on the other hand, provide high-temporal-resolution motion cues and excel in challenging…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Qianang Zhou , Junhui Hou , Meiyi Yang , Yongjian Deng , Youfu Li , Junlin Xiong

We propose a novel video frame interpolation algorithm based on asymmetric bilateral motion estimation (ABME), which synthesizes an intermediate frame between two input frames. First, we predict symmetric bilateral motion fields to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Junheum Park , Chul Lee , Chang-Su Kim

Event cameras have recently gained significant traction since they open up new avenues for low-latency and low-power solutions to complex computer vision problems. To unlock these solutions, it is necessary to develop algorithms that can…

Computer Vision and Pattern Recognition · Computer Science 2023-09-28 Federico Paredes-Vallés , Kirk Y. W. Scheper , Christophe De Wagter , Guido C. H. E. de Croon

We propose to incorporate feature correlation and sequential processing into dense optical flow estimation from event cameras. Modern frame-based optical flow methods heavily rely on matching costs computed from feature correlation. In…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Mathias Gehrig , Mario Millhäusler , Daniel Gehrig , Davide Scaramuzza

Recent progress in large-scale text-to-video (T2V) and image-to-video (I2V) diffusion models has greatly enhanced video generation, especially in terms of keyframe interpolation. However, current image-to-video diffusion models, while…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Serin Yang , Taesung Kwon , Jong Chul Ye

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

Inspired by the complementarity between conventional frame-based and bio-inspired event-based cameras, we propose a multi-modal based approach to fuse visual cues from the frame- and event-domain to enhance the single object tracking…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Jiqing Zhang , Xin Yang , Yingkai Fu , Xiaopeng Wei , Baocai Yin , Bo Dong

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Daniel Gehrig , Antonio Loquercio , Konstantinos G. Derpanis , Davide Scaramuzza

Deriving sophisticated 3D motions from sparse keyframes is a particularly challenging problem, due to continuity and exceptionally skeletal precision. The action features are often derivable accurately from the full series of keyframes, and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Clinton Ansun Mo , Kun Hu , Chengjiang Long , Zhiyong Wang

Video frame interpolation (VFI) works generally predict intermediate frame(s) by first estimating the motion between inputs and then warping the inputs to the target time with the estimated motion. This approach, however, is not optimal…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Dawit Mureja Argaw , In So Kweon

Event camera is an emerging bio-inspired vision sensors that report per-pixel brightness changes asynchronously. It holds noticeable advantage of high dynamic range, high speed response, and low power budget that enable it to best capture…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Zhanpeng Shao , Wen Zhou , Wuzhen Wang , Jianyu Yang , Youfu Li

Event cameras are advantageous for tasks that require vision sensors with low-latency and sparse output responses. However, the development of deep network algorithms using event cameras has been slow because of the lack of large labelled…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Joachim Ott , Zuowen Wang , Shih-Chii Liu

Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency. In practice, visible cameras can better…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Xiao Wang , Jianing Li , Lin Zhu , Zhipeng Zhang , Zhe Chen , Xin Li , Yaowei Wang , Yonghong Tian , Feng Wu

Event cameras are dynamic vision sensors inspired by the biological retina, characterized by their high dynamic range, high temporal resolution, and low power consumption. These features make them capable of perceiving 3D environments even…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Hoonhee Cho , Jae-Young Kang , Kuk-Jin Yoon

Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption. Despite these advantages, event cameras cannot be directly applied to…

Computer Vision and Pattern Recognition · Computer Science 2022-11-02 Jinjin Gu , Jinan Zhou , Ringo Sai Wo Chu , Yan Chen , Jiawei Zhang , Xuanye Cheng , Song Zhang , Jimmy S. Ren

Video frame interpolation is a challenging problem because there are different scenarios for each video depending on the variety of foreground and background motion, frame rate, and occlusion. It is therefore difficult for a single network…

Computer Vision and Pattern Recognition · Computer Science 2020-04-03 Myungsub Choi , Janghoon Choi , Sungyong Baik , Tae Hyun Kim , Kyoung Mu Lee
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