VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control

Image quality assessment: from error visibility to structural similarity

Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004 · 2004

Earlier work this paper cites.

A benchmark dataset and evaluation methodology for video object segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition . 724–732

Federico Perazzi, Jordi Pont-Tuset, Brian McWilliams, Luc Van Gool, Markus Gross, and Alexander Sorkine-Hornung. 2016 · 2016

Earlier work this paper cites.

Video-to-Video Synthesis. In Advances in Neural Information Processing Systems , S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, and R. Garnett (Eds.), Vol. 31. Curran Associates, Inc

Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Guilin Liu, Andrew Tao, Jan Kautz, and Bryan Catanzaro. 2018 · 2018

Earlier work this paper cites.

Youtube-vos: Sequence-to-sequence video object segmentation. In Proceedings of the European conference on computer vision (ECCV) . 585–601

Ning Xu, Linjie Yang, Yuchen Fan, Jianchao Yang, Dingcheng Yue, Yuchen Liang, Brian Price, Scott Cohen, and Thomas Huang. 2018 · 2018

Earlier work this paper cites.

The unreasonable effectiveness of deep features as a perceptual metric. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 586–595

Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang. 2018 · 2018

Earlier work this paper cites.

Learnable gated temporal shift module for deep video inpainting

Original

Ya-Liang Chang, Zhe Yu Liu, Kuan-Ying Lee, and Winston Hsu. 2019b · 2019

Earlier work this paper cites.

Deep video inpainting. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 5792–5801

Dahun Kim, Sanghyun Woo, Joon-Young Lee, and In So Kweon. 2019 · 2019

Earlier work this paper cites.

Copy-and-paste networks for deep video inpainting. In Proceedings of the IEEE/CVF international conference on computer vision . 4413–4421

Sungho Lee, Seoung Wug Oh, DaeYeun Won, and Seon Joo Kim. 2019 · 2019

Earlier work this paper cites.

Video inpainting by jointly learning temporal structure and spatial details. In Proceedings of the AAAI conference on artificial intelligence , Vol. 33. 5232–5239

Chuan Wang, Haibin Huang, Xiaoguang Han, and Jue Wang. 2019 · 2019

Earlier work this paper cites.

Deep flow-guided video inpainting. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 3723–3732

Rui Xu, Xiaoxiao Li, Bolei Zhou, and Chen Change Loy. 2019 · 2019

Earlier work this paper cites.

Flow-edge guided video completion. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XII 16 . Springer, 713–729

Chen Gao, Ayush Saraf, Jia-Bin Huang, and Johannes Kopf. 2020 · 2020

Earlier work this paper cites.

Proposal-based video completion. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXVII 16 . Springer, 38–54

Yuan-Ting Hu, Heng Wang, Nicolas Ballas, Kristen Grauman, and Alexander G Schwing. 2020 · 2020

Earlier work this paper cites.

Short-term and long-term context aggregation network for video inpainting. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part IV 16 . Springer, 728–743

Ang Li, Shanshan Zhao, Xingjun Ma, Mingming Gong, Jianzhong Qi, Rui Zhang, Dacheng Tao, and Ramamohanarao Kotagiri. 2020 · 2020

Earlier work this paper cites.

Raft: Recurrent all-pairs field transforms for optical flow. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16 . Springer, 402–419

Zachary Teed and Jia Deng. 2020 · 2020

Earlier work this paper cites.

Learning joint spatial-temporal transformations for video inpainting. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XVI 16 . Springer, 528–543

Yanhong Zeng, Jianlong Fu, and Hongyang Chao. 2020 · 2020

Earlier work this paper cites.

Decoupled spatial-temporal transformer for video inpainting

Original

Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu Sun, Xiaogang Wang, Jifeng Dai, and Hongsheng Li. 2021 · 2021

Earlier work this paper cites.

GODIVA: Generating open-domain videos from natural descriptions

Original

Chenfei Wu, Lun Huang, Qianxi Zhang, Binyang Li, Lei Ji, Fan Yang, Guillermo Sapiro, and Nan Duan. 2021 · 2021

Earlier work this paper cites.

Progressive temporal feature alignment network for video inpainting. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 16448–16457

Xueyan Zou, Linjie Yang, Ding Liu, and Yong Jae Lee. 2021 · 2021

Earlier work this paper cites.

EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations. In Proceedings of the Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks

Ahmad Darkhalil, Dandan Shan, Bin Zhu, Jian Ma, Amlan Kar, Richard Higgins, Sanja Fidler, David Fouhey, and Dima Damen. 2022 · 2022

Earlier work this paper cites.

Towards an end-to-end framework for flow-guided video inpainting. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 17562–17571

Zhen Li, Cheng-Ze Lu, Jianhua Qin, Chun-Le Guo, and Ming-Ming Cheng. 2022 · 2022

Earlier work this paper cites.

High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 10684–10695

Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022

Earlier work this paper cites.

Stable Diffusion 2 Inpainting

Robin Rombach and Patrick Esser. 2022 · 2022

Cited alongside, same era.

Laion-5b: An open large-scale dataset for training next generation image-text models

Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022

Cited alongside, same era.

Blended latent diffusion

Omri Avrahami, Ohad Fried, and Dani Lischinski. 2023 · 2023

Cited alongside, same era.

Improving image generation with better captions

James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, et al · 2023

Cited alongside, same era.

Stable video diffusion: Scaling latent video diffusion models to large datasets

Original

Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, et al · 2023

Cited alongside, same era.

CogVideoX-LoRA-Wallace_and_Gromit

Cseti. 2024 · 2024

Later among the works it cites.

ViViD: Video Virtual Try-on using Diffusion Models

Original

Zixun Fang, Wei Zhai, Aimin Su, Hongliang Song, Kai Zhu, Mao Wang, Yu Chen, Zhiheng Liu, Yang Cao, and Zheng-Jun Zha. 2024 · 2024

Later among the works it cites.

I2v-adapter: A general image-to-video adapter for diffusion models. In ACM SIGGRAPH 2024 Conference Papers . 1–12

Xun Guo, Mingwu Zheng, Liang Hou, Yuan Gao, Yufan Deng, Pengfei Wan, Di Zhang, Yufan Liu, Weiming Hu, Zhengjun Zha, et al · 2024

Later among the works it cites.

Brushnet: A plug-and-play image inpainting model with decomposed dual-branch diffusion

Original

Xuan Ju, Xian Liu, Xintao Wang, Yuxuan Bian, Ying Shan, and Qiang Xu. 2024 · 2024

Later among the works it cites.

KLING SPARK YOUR IMAGINATION

Kuaishou. 2024 · 2024

Later among the works it cites.