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Conventional approaches for video captioning leverage a variety of offline-extracted features to generate captions. Despite the availability of various offline-feature-extractors that offer diverse information from different perspectives,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Tian-Zi Niu , Zhen-Duo Chen , Xin Luo , Xin-Shun Xu

Advances in diffusion-based video generation models, while significantly improving human animation, poses threats of misuse through the creation of fake videos from a specific person's photo and text prompts. Recent efforts have focused on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Duc Vu , Anh Nguyen , Chi Tran , Anh Tran

Real-time video frame interpolation (VFI) is very useful in video processing, media players, and display devices. We propose RIFE, a Real-time Intermediate Flow Estimation algorithm for VFI. To realize a high-quality flow-based VFI method,…

Computer Vision and Pattern Recognition · Computer Science 2022-07-14 Zhewei Huang , Tianyuan Zhang , Wen Heng , Boxin Shi , Shuchang Zhou

The problem of video inter-frame interpolation is an essential task in the field of image processing. Correctly increasing the number of frames in the recording while maintaining smooth movement allows to improve the quality of played video…

Computer Vision and Pattern Recognition · Computer Science 2021-06-02 Malwina Kubas , Grzegorz Sarwas

Video inbetweening creates smooth and natural transitions between two image frames, making it an indispensable tool for video editing and long-form video synthesis. Existing works in this domain are unable to generate large, complex, or…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Maham Tanveer , Yang Zhou , Simon Niklaus , Ali Mahdavi Amiri , Hao Zhang , Krishna Kumar Singh , Nanxuan Zhao

Text-to-video (T2V) diffusion models have rapidly advanced, yet generations still occasionally fail in practice, such as low text-video alignment or low perceptual quality. Since diffusion sampling is non-deterministic, it is difficult to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Kwon Byung-Ki , Sohwi Lim , Nam Hyeon-Woo , Moon Ye-Bin , Tae-Hyun Oh

While large deep neural networks excel at general video analytics tasks, the significant demand on computing capacity makes them infeasible for real-time inference on resource-constrained end cam-eras. In this paper, we propose an…

Multimedia · Computer Science 2023-09-01 Yuxin Kong , Peng Yang , Yan Cheng

Video Large Language Models (Video-LLMs) have shown strong video understanding, yet their application to long-form videos remains constrained by limited context windows. A common workaround is to compress long videos into a handful of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Yun Wang , Long Zhang , Jingren Liu , Jiaqi Yan , Zhanjie Zhang , Jiahao Zheng , Ao Ma , Run Ling , Xun Yang , Dapeng Wu , Xiangyu Chen , Xuelong Li

A fitting soundtrack can help a video better convey its content and provide a better immersive experience. This paper introduces a novel approach utilizing self-supervised learning and contrastive learning to automatically recommend audio…

Multimedia · Computer Science 2025-03-10 Shimiao Liu , Alexander Lerch

Precise camera pose control is crucial for video generation with diffusion models. Existing methods require fine-tuning with additional datasets containing paired videos and camera pose annotations, which are both data-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Zhenghong Zhou , Jie An , Jiebo Luo

Fast neuromorphic event-based vision sensors (Dynamic Vision Sensor, DVS) can be combined with slower conventional frame-based sensors to enable higher-quality inter-frame interpolation than traditional methods relying on fixed motion…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Adam Radomski , Andreas Georgiou , Thomas Debrunner , Chenghan Li , Luca Longinotti , Minwon Seo , Moosung Kwak , Chang-Woo Shin , Paul K. J. Park , Hyunsurk Eric Ryu , Kynan Eng

Video-to-video diffusion models achieve impressive single-turn editing performance, but practical editing workflows are inherently iterative. When edits are applied sequentially, existing models treat each turn independently, often causing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Dohun Lee , Chun-Hao Paul Huang , Xuelin Chen , Jong Chul Ye , Duygu Ceylan , Hyeonho Jeong

Effectively extracting inter-frame motion and appearance information is important for video frame interpolation (VFI). Previous works either extract both types of information in a mixed way or elaborate separate modules for each type of…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Guozhen Zhang , Yuhan Zhu , Haonan Wang , Youxin Chen , Gangshan Wu , Limin Wang

Previous methods for Video Frame Interpolation (VFI) have encountered challenges, notably the manifestation of blur and ghosting effects. These issues can be traced back to two pivotal factors: unavoidable motion errors and misalignment in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Guangyang Wu , Xin Tao , Changlin Li , Wenyi Wang , Xiaohong Liu , Qingqing Zheng

Diffusion models have obtained substantial progress in image-to-video generation. However, in this paper, we find that these models tend to generate videos with less motion than expected. We attribute this to the issue called conditional…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Min Zhao , Hongzhou Zhu , Chendong Xiang , Kaiwen Zheng , Chongxuan Li , Jun Zhu

Video virtual try-on aims to transfer a clothing item onto the video of a target person. Directly applying the technique of image-based try-on to the video domain in a frame-wise manner will cause temporal-inconsistent outcomes while…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Zixun Fang , Wei Zhai , Aimin Su , Hongliang Song , Kai Zhu , Mao Wang , Yu Chen , Zhiheng Liu , Yang Cao , Zheng-Jun Zha

The event camera, benefiting from its high dynamic range and low latency, provides performance gain for low-light image enhancement. Unlike frame-based cameras, it records intensity changes with extremely high temporal resolution, capturing…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Chunyan She , Fujun Han , Chengyu Fang , Shukai Duan , Lidan Wang

Recently, the remarkable success of pre-trained Vision Transformers (ViTs) from image-text matching has sparked an interest in image-to-video adaptation. However, most current approaches retain the full forward pass for each frame, leading…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guozhen Zhang , Jingyu Liu , Shengming Cao , Xiaotong Zhao , Kevin Zhao , Kai Ma , Limin Wang

We consider the problem of generating plausible and diverse video sequences, when we are only given a start and an end frame. This task is also known as inbetweening, and it belongs to the broader area of stochastic video generation, which…

Computer Vision and Pattern Recognition · Computer Science 2019-06-05 Yunpeng Li , Dominik Roblek , Marco Tagliasacchi

State-of-the-art frame interpolation methods generate intermediate frames by inferring object motions in the image from consecutive key-frames. In the absence of additional information, first-order approximations, i.e. optical flow, must be…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Stepan Tulyakov , Daniel Gehrig , Stamatios Georgoulis , Julius Erbach , Mathias Gehrig , Yuanyou Li , Davide Scaramuzza
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