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For video frame interpolation (VFI), existing deep-learning-based approaches strongly rely on the ground-truth (GT) intermediate frames, which sometimes ignore the non-unique nature of motion judging from the given adjacent frames. As a…

Computer Vision and Pattern Recognition · Computer Science 2022-03-22 Kun Zhou , Wenbo Li , Xiaoguang Han , Jiangbo Lu

Recent works have shown the ability of Implicit Neural Representations (INR) to carry meaningful representations of signal derivatives. In this work, we leverage this property to perform Video Frame Interpolation (VFI) by explicitly…

Computer Vision and Pattern Recognition · Computer Science 2022-06-23 Weihao Zhuang , Tristan Hascoet , Ryoichi Takashima , Tetsuya Takiguchi

In this work, we propose a new diffusion-based method for video frame interpolation (VFI), in the context of traditional hand-made animation. We introduce three main contributions: The first is that we explicitly handle the interpolation…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Victor Fonte Chavez , Claudia Esteves , Jean-Bernard Hayet

Despite the recent progress, existing frame interpolation methods still struggle with processing extremely high resolution input and handling challenging cases such as repetitive textures, thin objects, and large motion. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Junhwa Hur , Charles Herrmann , Saurabh Saxena , Janne Kontkanen , Wei-Sheng Lai , Yichang Shih , Michael Rubinstein , David J. Fleet , Deqing Sun

Video frame interpolation (VFI) aims to generate predictive frames by warping learnable motions from the bidirectional historical references. Most existing works utilize spatio-temporal semantic information extractor to realize motion…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Meiqin Liu , Chenming Xu , Chao Yao , Chunyu Lin , Yao Zhao

Event cameras asynchronously capture brightness changes with microsecond latency, offering exceptional temporal precision but suffering from severe noise and signal inconsistencies. Unlike conventional signals, events carry state…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Jinze Chen , Wei Zhai , Yang Cao , Bin Li , Zheng-Jun Zha

Currently, most low-light image enhancement methods only consider information from a single view, neglecting the correlation between cross-view information. Therefore, the enhancement results produced by these methods are often…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Linlin Hu , Ao Sun , Shijie Hao , Richang Hong , Meng Wang

Event cameras are an interesting visual exteroceptive sensor that reacts to brightness changes rather than integrating absolute image intensities. Owing to this design, the sensor exhibits strong performance in situations of challenging…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Runze Yuan , Tao Liu , Zijia Dai , Yi-Fan Zuo , Laurent Kneip

Event cameras excel in capturing high-contrast scenes and dynamic objects, offering a significant advantage over traditional frame-based cameras. Despite active research into leveraging event cameras for semantic segmentation, generating…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Hoonhee Cho , Sung-Hoon Yoon , Hyeokjun Kweon , Kuk-Jin Yoon

Event cameras are bio-inspired sensors that mimic the human retina by responding to brightness changes in the scene. They generate asynchronous spike-based outputs at microsecond resolution, providing advantages over traditional cameras…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Suman Ghosh , Guillermo Gallego

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

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Guillermo Gallego , Jon E. A. Lund , Elias Mueggler , Henri Rebecq , Tobi Delbruck , Davide Scaramuzza

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. This paper presents a solution to the problem of 3D…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Yi Zhou , Guillermo Gallego , Henri Rebecq , Laurent Kneip , Hongdong Li , Davide Scaramuzza

Frame interpolation is an essential video processing technique that adjusts the temporal resolution of an image sequence. While deep learning has brought great improvements to the area of video frame interpolation, techniques that make use…

Computer Vision and Pattern Recognition · Computer Science 2022-10-27 Simon Niklaus , Ping Hu , Jiawen Chen

Interactive Video Object Segmentation (iVOS) is a challenging task that requires real-time human-computer interaction. To improve the user experience, it is important to consider the user's input habits, segmentation quality, running time…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Kexin Li , Tao Jiang , Zongxin Yang , Yi Yang , Yueting Zhuang , Jun Xiao

Video frame interpolation has long been challenged by limited controllability and interactivity, especially in scenarios involving fast, highly non-linear, and fine-grained motion. Although recent interactive interpolation methods have made…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuchen Deng , Xiuyang Wu , Hai-Tao Zheng , Jie Wang , Feidiao Yang , Yuxing Han

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

Compared to conventional cameras, event cameras provide a high dynamic range and low latency, offering greater robustness to rapid motion and challenging lighting conditions. Although the potential of event cameras for visual place…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Therese Joseph , Tobias Fischer , Michael Milford

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

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