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Related papers: OutDreamer: Video Outpainting with a Diffusion Tra…

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Video object removal and inpainting are critical tasks in the fields of computer vision and multimedia processing, aimed at restoring missing or corrupted regions in video sequences. Traditional methods predominantly rely on flow-based…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Jie Liu , Zheng Hui

Many existing video inpainting algorithms utilize optical flows to construct the corresponding maps and then propagate pixels from adjacent frames to missing areas by mapping. Despite the effectiveness of the propagation mechanism, they…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Xian Wu , Chang Liu

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Xiaowen Li , Haolan Xue , Peiran Ren , Liefeng Bo

Video outpainting aims to adequately complete missing areas at the edges of video frames. Compared to image outpainting, it presents an additional challenge as the model should maintain the temporal consistency of the filled area. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-01-22 Fanda Fan , Chaoxu Guo , Litong Gong , Biao Wang , Tiezheng Ge , Yuning Jiang , Chunjie Luo , Jianfeng Zhan

Video outpainting presents a unique challenge of extending the borders while maintaining consistency with the given content. In this paper, we suggest the use of video inpainting models that excel in object flow learning and reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Sangwoo Youn , Minji Lee , Nokap Tony Park , Yeonggyoo Jeon , Taeyoung Na

M3DDM provides a computationally efficient framework for video outpainting via latent diffusion modeling. However, it exhibits significant quality degradation -- manifested as spatial blur and temporal inconsistency -- under challenging…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Takuya Murakawa , Takumi Fukuzawa , Ning Ding , Toru Tamaki

Layout generation is a foundation task of graphic design, which requires the integration of visual aesthetics and harmonious expression of content delivery. However, existing methods still face challenges in generating precise and visually…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yu Li , Yifan Chen , Gongye Liu , Fei Yin , Qingyan Bai , Jie Wu , Hongfa Wang , Ruihang Chu , Yujiu Yang

Due to lack of fully publicly available text-to-video models, current video editing methods tend to build on pre-trained text-to-image generation models, however, they still face grand challenges in dealing with the local editing of video…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Deyin Liu , Lin Yuanbo Wu , Xianghua Xie

Point tracking aims to localize corresponding points across video frames, serving as a fundamental task for 4D reconstruction, robotics, and video editing. Existing methods commonly rely on shallow convolutional backbones such as ResNet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Soowon Son , Honggyu An , Chaehyun Kim , Hyunah Ko , Jisu Nam , Dahyun Chung , Siyoon Jin , Jung Yi , Jaewon Min , Junhwa Hur , Seungryong Kim

Recent progress in diffusion models has significantly advanced the field of human image animation. While existing methods can generate temporally consistent results for short or regular motions, significant challenges remain, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Shen Zheng , Jiaran Cai , Yuansheng Guan , Shenneng Huang , Xingpei Ma , Junjie Cao , Hanfeng Zhao , Qiang Zhang , Shunsi Zhang , Xiao-Ping Zhang

Video outpainting extends a video beyond its original boundaries by synthesizing missing border content. Compared with image outpainting, it requires not only per-frame spatial plausibility but also long-range temporal coherence, especially…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yueming Pan , Ruoyu Feng , Jianmin Bao , Chong Luo , Nanning Zheng

Diffusion Transformer(DiT)-based generation models have achieved remarkable success in video generation. However, their inherent computational demands pose significant efficiency challenges. In this paper, we exploit the inherent temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zhihang Yuan , Rui Xie , Yuzhang Shang , Hanling Zhang , Siyuan Wang , Shengen Yan , Guohao Dai , Yu Wang

Video outpainting aims to expand the visible content of a video beyond the original frame boundaries while preserving spatial fidelity and temporal coherence across frames. Existing methods primarily rely on large-scale generative models,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Inseok Jeon , Minhyeok Lee , Seunghoon Lee , Minseok Kang , Suhwan Cho , Sangyoun Lee

Scene extrapolation -- the idea of generating novel views by flying into a given image -- is a promising, yet challenging task. For each predicted frame, a joint inpainting and 3D refinement problem has to be solved, which is ill posed and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Shengqu Cai , Eric Ryan Chan , Songyou Peng , Mohamad Shahbazi , Anton Obukhov , Luc Van Gool , Gordon Wetzstein

Generating complete 360-degree panoramas from narrow field of view images is ongoing research as omnidirectional RGB data is not readily available. Existing GAN-based approaches face some barriers to achieving higher quality output, and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Tianhao Wu , Chuanxia Zheng , Tat-Jen Cham

Despite recent advances in UNet-based image editing, methods for shape-aware object editing in high-resolution images are still lacking. Compared to UNet, Diffusion Transformers (DiT) demonstrate superior capabilities to effectively capture…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Kunyu Feng , Yue Ma , Bingyuan Wang , Chenyang Qi , Haozhe Chen , Qifeng Chen , Zeyu Wang

Video generation has drawn significant interest recently, pushing the development of large-scale models capable of producing realistic videos with coherent motion. Due to memory constraints, these models typically generate short video…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Idan Kligvasser , Regev Cohen , George Leifman , Ehud Rivlin , Michael Elad

Recent video inpainting methods have achieved encouraging improvements by leveraging optical flow to guide pixel propagation from reference frames either in the image space or feature space. However, they would produce severe artifacts in…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Chaohao Xie , Kai Han , Kwan-Yee K. Wong

Video outpainting is a challenging task, aiming at generating video content outside the viewport of the input video while maintaining inter-frame and intra-frame consistency. Existing methods fall short in either generation quality or…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Fu-Yun Wang , Xiaoshi Wu , Zhaoyang Huang , Xiaoyu Shi , Dazhong Shen , Guanglu Song , Yu Liu , Hongsheng Li

In this work, we rethink the approach to video super-resolution by introducing a method based on the Diffusion Posterior Sampling framework, combined with an unconditional video diffusion transformer operating in latent space. The video…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Zhihao Zhan , Wang Pang , Xiang Zhu , Yechao Bai
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