computer-vision-1

Video Editing

3260 papers • 126 benchmarks • 313 datasets

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i

Use these libraries to find video-editing-1 models and implementations

zhang-tao-whu/DVIS

3 papers 118

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Subtasks

Video Temporal Consistency

Most implemented papers

LEO: Generative Latent Image Animator for Human Video Synthesis

Y. Qiao, Bo Dai, Xinyuan Chen, Yaohui Wang, Xin Ma, A. Dantcheva•Fri May 05 2023

Extensive quantitative and qualitative analysis suggests that LEO significantly improves coherent synthesis of human videos over previous methods on the datasets TaichiHD, FaceForensics and CelebV-HQ, as well as content-preserving video editing.

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Point-to-Point Video Generation

Hwann-Tzong Chen, Min Sun, Tsun-Hsuan Wang, Y. Cheng, Chieh Hubert Lin•Thu Apr 04 2019

This work introduces point-to-point video generation that controls the generation process with two control points: the targeted start- and end-frames and proposes to maximize the modified variational lower bound of conditional data likelihood under a skip-frame training strategy.

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SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos

Bernard Ghanem, T. Moeslund, A. Deliège, A. Cioppa, Silvio Giancola, M. J. Seikavandi, J. Dueholm, Kamal Nasrollahi, Marc Van Droogenbroeck•Wed Nov 25 2020

This work proposes SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production, and extends current tasks in the realm of soccer to include action spotting, camera shot segmentation with boundary detection, and a novel replay grounding task.

184 0

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BodyNet: Volumetric Inference of 3D Human Body Shapes

Gül Varol, I. Laptev, Jimei Yang, Duygu Ceylan, Bryan C. Russell, C. Schmid, Ersin Yumer•Thu Apr 12 2018

BodyNet is an end-to-end trainable network that benefits from a volumetric 3D loss, a multi-view re-projection loss, and intermediate supervision of 2D pose, 2D body part segmentation, and 3D pose and achieves state-of-the-art performance.

449 0

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Free-Form Video Inpainting With 3D Gated Convolution and Temporal PatchGAN

Winston H. Hsu, Ya-Liang Chang, Zhe Yu Liu, Kuan-Ying Lee•Mon Apr 22 2019

A deep learning based free-form video inpainting model is introduced, with proposed 3D gated convolutions to tackle the uncertainty offree-form masks and a novel Temporal PatchGAN loss to enhance temporal consistency.

205 0

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Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video

M. Zollhöfer, A. Tewari, C. Theobalt, Vladislav Golyanik, Christoph Lassner, E. Tretschk•Mon Dec 21 2020

Non-Rigid Neural Radiance Fields (NR-NeRF), a reconstruction and novel view synthesis approach for general non-rigid dynamic scenes, takes RGB images of a dynamic scene as input, and creates a high-quality space-time geometry and appearance representation.

591 0

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Feature Combination Meets Attention: Baidu Soccer Embeddings and Transformer based Temporal Detection

Le Kang, Zhiyu Cheng, Bo He, Jingyu Xin•Sun Jun 27 2021

This tech report presents a two-stage paradigm to detect what and when events happen in soccer broadcast videos, fine-tune multiple action recognition models on soccer data to extract high-level semantic features, and design a transformer based temporal detection module to locate the target events.

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Combating Online Misinformation Videos: Characterization, Detection, and Future Directions

Juan Cao, Yuyan Bu, Qiang Sheng, Peng Qi, Danding Wang, Jintao Li•Mon Feb 06 2023

This survey analyzes and characterize the misinformation video from three levels including signal, semantic, and intent and systematically reviews existing works for detection from features of various modalities to techniques for clue integration.

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Layered neural atlases for consistent video editing

Oliver Wang, Tali Dekel, Yoni Kasten, Dolev Ofri-Amar•Wed Sep 22 2021

A method that decomposes, and "unwraps", an input video into a set of layered 2D atlases, each providing a unified representation of the appearance of an object (or background) over the video, which does not require any prior 3D knowledge about scene geometry or camera poses.

184 0

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FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models

Hao Zhang, Yanbo Xu, Tianyuan Dai, Yu-Wing, Tai Chi-Keung Tang•Wed May 31 2023

The proposed Face Diffusion NeRF (FaceDNeRF), a new generative method to reconstruct high-quality Face NeRFs from single images, complete with semantic editing and relighting capabilities, achieves exceptionally realistic results and unprecedented flexibility in editing compared with state-of-the-art 3D face reconstruction and editing methods.

7 0

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