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Facial video editing has become increasingly important for content creators, enabling the manipulation of facial expressions and attributes. However, existing models encounter challenges such as poor editing quality, high computational…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Tharun Anand , Aryan Garg , Kaushik Mitra

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

Multimedia generation approaches occupy a prominent place in artificial intelligence research. Text-to-image models achieved high-quality results over the last few years. However, video synthesis methods recently started to develop. This…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Vladimir Arkhipkin , Zein Shaheen , Viacheslav Vasilev , Elizaveta Dakhova , Andrey Kuznetsov , Denis Dimitrov

Existing video frame interpolation (VFI) methods often adopt a frame-centric approach, processing videos as independent short segments (e.g., triplets), which leads to temporal inconsistencies and motion artifacts. To overcome this, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Xinyu Peng , Han Li , Yuyang Huang , Ziyang Zheng , Yaoming Wang , Xin Chen , Wenrui Dai , Chenglin Li , Junni Zou , Hongkai Xiong

Video frame interpolation aims to generate high-quality intermediate frames from boundary frames and increase frame rate. While existing linear, symmetric and nonlinear models are used to bridge the gap from the lack of inter-frame motion,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-19 Chenyang Shi , Hanxiao Liu , Jing Jin , Wenzhuo Li , Yuzhen Li , Boyi Wei , Yibo Zhang

Real-world videos often extend over thousands of frames. Existing generative video super-resolution (VSR) approaches, however, face two persistent challenges when processing long sequences: (1) inefficiency due to the heavy cost of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Ziqing Zhang , Kai Liu , Zheng Chen , Xi Li , Yucong Chen , Bingnan Duan , Linghe Kong , Yulun Zhang

Text-to-image (T2I) diffusion models achieve state-of-the-art results in image synthesis and editing. However, leveraging such pretrained models for video editing is considered a major challenge. Many existing works attempt to enforce…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Nathaniel Cohen , Vladimir Kulikov , Matan Kleiner , Inbar Huberman-Spiegelglas , Tomer Michaeli

Intrinsic Image Decomposition (IID) separates an image into albedo and shading components. It is a core step in many real-world applications, such as relighting and material editing. Existing IID models achieve good results, but often use a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Mithlesh Singla , Seema Kumari , Shanmuganathan Raman

Video-to-video translation aims to generate video frames of a target domain from an input video. Despite its usefulness, the existing networks require enormous computations, necessitating their model compression for wide use. While there…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Chaeyeon Chung , Yeojeong Park , Seunghwan Choi , Munkhsoyol Ganbat , Jaegul Choo

Large-scale text-to-video models have shown remarkable abilities, but their direct application in video editing remains challenging due to limited available datasets. Current video editing methods commonly require per-video fine-tuning of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Zhenghao Zhang , Zuozhuo Dai , Long Qin , Weizhi Wang

Diffusion models have made tremendous progress in text-driven image and video generation. Now text-to-image foundation models are widely applied to various downstream image synthesis tasks, such as controllable image generation and image…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Fengyuan Shi , Jiaxi Gu , Hang Xu , Songcen Xu , Wei Zhang , Limin Wang

Current video generation models perform well at single-shot synthesis but struggle with multi-shot videos, facing critical challenges in maintaining character and background consistency across shots and flexibly generating videos of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Xiangyang Luo , Qingyu Li , Xiaokun Liu , Wenyu Qin , Miao Yang , Meng Wang , Pengfei Wan , Di Zhang , Kun Gai , Shao-Lun Huang

Our study introduces a new image-to-video generator called FashionFlow to generate fashion videos. By utilising a diffusion model, we are able to create short videos from still fashion images. Our approach involves developing and connecting…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Tasin Islam , Alina Miron , XiaoHui Liu , Yongmin Li

Recently, image-to-video (I2V) diffusion models have demonstrated impressive scene understanding and generative quality, incorporating image conditions to guide generation. However, these models primarily animate static images without…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Luis Denninger , Sina Mokhtarzadeh Azar , Juergen Gall

Diffusion and flow matching models have unlocked unprecedented capabilities for creative content creation, such as interactive image and streaming video generation. The growing demand for higher resolutions, frame rates, and context…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Brian Chao , Lior Yariv , Howard Xiao , Gordon Wetzstein

Infrared and visible video fusion is essential for achieving comprehensive perception in dynamic scenes. However, maintaining temporal consistency remains a formidable challenge. Conventional methods relying on optical flow often suffer…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Xingyuan Li , Haoyuan Xu , Shulin Li , Xiang Chen , Zhiying Jiang , Jinyuan Liu

Text-to-video (T2V) generation is a rapidly growing research area that aims to translate the scenes, objects, and actions within complex video text into a sequence of coherent visual frames. We present FlowZero, a novel framework that…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Yu Lu , Linchao Zhu , Hehe Fan , Yi Yang

In this paper, we introduce Fairy, a minimalist yet robust adaptation of image-editing diffusion models, enhancing them for video editing applications. Our approach centers on the concept of anchor-based cross-frame attention, a mechanism…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Bichen Wu , Ching-Yao Chuang , Xiaoyan Wang , Yichen Jia , Kapil Krishnakumar , Tong Xiao , Feng Liang , Licheng Yu , Peter Vajda

Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains constrained by severe inference costs. Compared with image generation, video synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Shitong Shao , Lichen Bai , Pengfei Wan , James Kwok , Zeke Xie

Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity changes rather than absolute intensity, the resulting data streams suffer from a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Gang Xu , Zhiyu Zhu , Junhui Hou
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