{"id":14112781,"url":"https://github.com/wentianli/awesome-video-editing","last_synced_at":"2025-08-01T15:32:55.205Z","repository":{"id":168923698,"uuid":"579546364","full_name":"wentianli/awesome-video-editing","owner":"wentianli","description":"A paper list of automatic video editing and its related computer vision tasks.","archived":false,"fork":false,"pushed_at":"2023-11-09T16:53:22.000Z","size":78,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"main","last_synced_at":"2024-04-12T10:15:32.476Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/wentianli.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2022-12-18T03:26:46.000Z","updated_at":"2023-05-29T06:09:52.000Z","dependencies_parsed_at":"2023-11-09T17:52:50.808Z","dependency_job_id":null,"html_url":"https://github.com/wentianli/awesome-video-editing","commit_stats":null,"previous_names":["wentianli/awesome-video-editing"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wentianli%2Fawesome-video-editing","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wentianli%2Fawesome-video-editing/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wentianli%2Fawesome-video-editing/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wentianli%2Fawesome-video-editing/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/wentianli","download_url":"https://codeload.github.com/wentianli/awesome-video-editing/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":228393577,"owners_count":17912861,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-14T10:03:55.378Z","updated_at":"2025-08-01T15:32:55.174Z","avatar_url":"https://github.com/wentianli.png","language":null,"funding_links":[],"categories":["Other Lists","Attribution"],"sub_categories":["TeX Lists","AI-Assisted CG Software"],"readme":"# awesome-video-editing [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\nA paper list on video editing (in a cinematographic sense) and its related computer vision tasks.\n\nThe papers are put into categories, in which there is unavoidably some overlapping and imprecision. I use some icons to mark several frequent application scenarios: 💬(talk/meeting), 💃(dance/performance), ⚽🏀🏌️🎾(sports), 🛒(ads/promotional videos), 🎬(movie), etc.\n\n\n*Note: This paper list does not include the works on image/video manipulation (e.g. content editing, object removal, video stylization).*\n\n🀄视频剪辑\n\n---\n## Text-based Video Editing\n**LLM-Powered or Instruction-based Editing.**\n- `[NeurIPS 2024 workshop]` Generative Timelines for Instructed Visual Assembly [[paper]](https://arxiv.org/abs/2411.12293) [[project page]](https://sites.google.com/kaust.edu.sa/timeline-assembler)\n- `[IUI 2024]` LAVE: LLM-Powered Agent Assistance and Language Augmentation for Video Editing [[paper]](https://arxiv.org/abs/2402.10294)\n\n**Using texts as input to automatically create video sequences from a collection of videos or images.**\n- `[arxiv 2025]` SKALD: Learning-Based Shot Assembly for Coherent Multi-Shot Video Creation [[paper]](https://arxiv.org/abs/2503.08010)\n- `[arxiv 2024]` Text-Video Multi-Grained Integration for Video Moment Montage [[paper]](https://arxiv.org/abs/2412.09276)\n- `[ICMR 2023]` Shot Retrieval and Assembly with Text Script for Video Montage Generation [[paper]](https://dl.acm.org/doi/10.1145/3591106.3592247) [[code]](https://github.com/RATVDemo/RATV)\n- `[MM 2022]` Transcript to Video: Efficient Clip Sequencing from Texts [[paper]](https://arxiv.org/abs/2107.11851) [[project page]](http://www.xiongyu.me/projects/transcript2video/)\n- `[CHI 2020]` Generating Audio-Visual Slideshows from Text Articles Using Word Concreteness [[paper]](https://dl.acm.org/doi/abs/10.1145/3313831.3376519)\n- `[TOG 2019]` Write-A-Video: Computational Video Montage from Themed Text [[paper]](https://dl.acm.org/doi/abs/10.1145/3355089.3356520)\n- `[TMM 2020]` Story-driven Video Editing [[paper]](https://ieeexplore.ieee.org/abstract/document/9257101)\n- `[IMX 2020]` Joint Attention for Automated Video Editing [[paper]](https://dl.acm.org/doi/abs/10.1145/3391614.3393656) 💬\n- `[UIST 2016]` QuickCut: An Interactive Tool for Editing Narrated Video [[paper]](https://dl.acm.org/doi/abs/10.1145/2984511.2984569)\n\n**Modifying the transcript of a speech to change the speech content or to remove filler words.**\n- `[TOG 2019]` Text-based Editing of Talking-head Video [[paper]](https://dl.acm.org/doi/abs/10.1145/3306346.3323028) 💬\n- `[TOG 2012]` Tools for Placing Cuts and Transitions in Interview Video [[paper]](https://dl.acm.org/doi/abs/10.1145/2185520.2185563) 💬\n\n\u003cbr/\u003e\n\n## Cutting and Sequencing Shots\n**To cut unedited videos into shots and/or to put them in an appropriate order.**\n- `[ICASSP 2024]` Audio Match Cutting: Finding and Creating Matching Audio Transitions in Movies and Videos [[paper]](https://ieeexplore.ieee.org/abstract/document/10447306) [[project page]](https://denfed.github.io/audiomatchcut/)\n- `[CVPR 2024]` Towards Automated Movie Trailer Generation [[paper]](https://arxiv.org/abs/2404.03477) 🎬\n- `[MM 2023]` A Reinforcement Learning-Based Automatic Video Editing [[paper]](https://arxiv.org/abs/2301.00135v2) 🎬\n- `[ICCV 2023 Workshop]` Representation Learning of Next Shot Selection for Vlog Editing [[paper]](https://cveu.github.io/2023/papers/31.pdf)\n- `[WACV 2023]` Match Cutting: Finding Cuts with Smooth Visual Transitions [[paper]](https://arxiv.org/abs/2210.05766) [[code]](https://github.com/netflix/matchcut) [[project page]](https://netflixtechblog.com/match-cutting-at-netflix-finding-cuts-with-smooth-visual-transitions-31c3fc14ae59?gi=8873f373fd1d) 🎬\n- `[ACCV 2022]` Multi-modal Segment Assemblage Network for Ad Video Editing with Importance-Coherence Reward [[paper]](https://arxiv.org/abs/2209.12164v1) [[code]](https://github.com/yunlong10/Ads-1k) 🛒\n- `[SAC 2022]` Automated Video Editing Based on Learned Styles Using LSTM-GAN [[paper]](https://dl.acm.org/doi/abs/10.1145/3477314.3507141) 💃\n- `[ICCV 2021 Workshop]` Learning Where To Cut From Edited Videos [[paper]](https://openaccess.thecvf.com/content/ICCV2021W/CVEU/html/Huang_Learning_Where_To_Cut_From_Edited_Videos_ICCVW_2021_paper.html)\n- `[ICCV 2021]` Learning to Cut by Watching Movies [[paper]](https://arxiv.org/abs/2108.04294) [[code \u0026 dataset]](https://github.com/PardoAlejo/LearningToCut) [[project page]](https://www.alejandropardo.net/publication/learning-to-cut/)\n- `[WACV 2018]` Learning Video-Story Composition via Recurrent Neural Network [[paper]](https://arxiv.org/abs/1801.10281)\n- `[arxiv 2018]` From Trailers to Storylines: An Efficient Way to Learn from Movies [[paper]](https://arxiv.org/abs/1806.05341) 🎬\n- `[CVPR 2016]` Video-Story Composition via Plot Analysis [[paper]](https://openaccess.thecvf.com/content_cvpr_2016/html/Choi_Video-Story_Composition_via_CVPR_2016_paper.html)\n\n\u003cbr/\u003e\n\n## Multi-Camera / Multi-Take Editing\n**To select video shots from multiple camera views or multiple takes of the same event.**\n- `[MIG 2023]` Real-time Computational Cinematographic Editing for Broadcasting of Volumetric-captured events: an Application to Ultimate Fighting [[paper]](https://dl.acm.org/doi/abs/10.1145/3623264.3624468) 🥊\n- `[TOG 2022]` PopStage: The Generation of Stage Cross-Editing Video Based on Spatio-Temporal Matching [[paper]](https://dl.acm.org/doi/abs/10.1145/3550454.3555467) [[project page]](https://w-dlee.github.io/popstage) 💃\n- `[ECCV 2022 Workshop]` Temporal and Contextual Transformer for Multi-Camera Editing of TV Shows [[paper]](https://arxiv.org/abs/2210.08737)\n- `[ICME 2021]` Reinforcement Learning Based Automatic Personal Mashup Generation [[paper]](https://www.computer.org/csdl/proceedings-article/icme/2021/09428357/1uim1GOOhtC)\n- `[TOMCCAP 2021]` Smart Director: An Event-Driven Directing System for Live Broadcasting [[paper]](https://dl.acm.org/doi/full/10.1145/3448981) ⚽\n- `[ICISP 2018]` Automatic Camera Selection in the Context of Basketball Game [[paper]](https://link.springer.com/chapter/10.1007/978-3-319-94211-7_9) 🏀\n- `[TOG 2017]` Computational Video Editing for Dialogue-Driven Scenes [[paper]](https://dl.acm.org/doi/abs/10.1145/3072959.3073653) 💬\n- `[ACE 2017]` Automatic System for Editing Dance Videos Recorded Using Multiple Cameras [[paper]](https://link.springer.com/chapter/10.1007/978-3-319-76270-8_47) 💃\n- `[TOG 2014]` Automatic Editing of Footage from Multiple Social Cameras [[paper]](https://dl.acm.org/doi/abs/10.1145/2601097.2601198)\n- `[CHI 2008]` Improving Meeting Capture by Applying Television Production Principles with Audio and Motion Detection [[paper]](https://dl.acm.org/doi/abs/10.1145/1357054.1357095) 💬\n- `[ICME 2007]` Automatic Multi-Modal Meeting Camera Selection for Video-Conferences and Meeting Browsers [[paper]](https://ieeexplore.ieee.org/abstract/document/4285090) 💬\n\n\u003cbr/\u003e\n\n## Video Summarization \u0026 Highlight Detection\n- `[CVPR 2023]` Collaborative Noisy Label Cleaner: Learning Scene-aware Trailers for Multi-modal Highlight Detection in Movies [[paper]](https://arxiv.org/abs/2303.14768) [[code]](https://github.com/TencentYoutuResearch/HighlightDetection-CLC) 🎬\n- `[NeurIPS 2022 Workshop]` Videogenic: Video Highlights via Photogenic Moments [[paper]](https://neuripscreativityworkshop.github.io/2022/papers/ml4cd2022_paper02.pdf) [[project page]](https://humanvideointeraction.github.io/videogenic/)\n- `[AutoUI 2021]` Automatic Generation of Road Trip Summary Video for Reminiscence and Entertainment using Dashcam Video [[paper]](https://dl.acm.org/doi/abs/10.1145/3409118.3475151)\n- `[MM 2021]` Automated Multi-Modal Video Editing for Ads Video [[paper]](https://dl.acm.org/doi/abs/10.1145/3474085.3479205) 🛒\n- `[MM 2021]` VideoDiscovery: An Automatic Short-Video Generation System for E-commerce Live-streaming [[paper]](https://dl.acm.org/doi/abs/10.1145/3474085.3478554) [[project page]](https://discovery.aliyun.com/index#/) 🛒\n- `[ECCV 2020]` Learning Trailer Moments in Full-Length Movies [[paper]](https://arxiv.org/abs/2008.08502) 🎬\n- `[MMAsia 2019]` Domain Specific and Idiom Adaptive Video Summarization [[paper]](https://dl.acm.org/doi/abs/10.1145/3338533.3366603) 🛒\n- `[MM 2019]` Personalized Video Summarization with Idiom Adaptation [[paper]](https://dl.acm.org/doi/pdf/10.1145/3343031.3350584) 🛒\n- `[MM 2019]` Generating 1 Minute Summaries of Day Long Egocentric Videos [[paper]](https://dl.acm.org/doi/abs/10.1145/3343031.3350880) [[code]](https://github.com/anuj-rathore/Generating-One-Minute-Summaries)\n- `[TMM 2019]` Automatic Curation of Sports Highlights Using Multimodal Excitement Features [[paper]](https://ieeexplore.ieee.org/abstract/document/8491305) 🏌️🎾\n- `[ICNC-FSKD 2019]` Towards Data-Driven Automatic Video Editing [[paper]](https://arxiv.org/abs/1907.07345) 🎬\n- `[CVPR 2018 Workshop]` The Excitement of Sports: Automatic Highlights Using Audio/Visual Cues [[paper]](https://openaccess.thecvf.com/content_cvpr_2018_workshops/w49/html/Merler_The_Excitement_of_CVPR_2018_paper.html) 🏌️🎾\n- `[CVPR 2013]` Story-Driven Summarization for Egocentric Video [[paper]](https://openaccess.thecvf.com/content_cvpr_2013/html/Lu_Story-Driven_Summarization_for_2013_CVPR_paper.html)\n- `[MM 2003]` AVE: automated home video editing [[paper]](https://dl.acm.org/doi/abs/10.1145/957013.957121)\n\n\u003cbr/\u003e\n\n## Other Forms of Editing\n- `[arxiv 2024]` MatchDiffusion: Training-free Generation of Match-cuts [[paper]](https://arxiv.org/abs/2411.18677) [[project page]](https://matchdiffusion.github.io/)\n- `[arxiv 2024]` VCoME: Verbal Video Composition with Multimodal Editing Effects [[paper]](https://arxiv.org/abs/2407.04697) [[code]](https://github.com/LetsGoFir/VCoME) 💬\n- `[CHI 2024]` ChunkyEdit: Text-first video interview editing via chunking [[paper]](https://dl.acm.org/doi/10.1145/3613904.3642667) 💬\n- `[IUI 2024]` ExpressEdit: Video Editing with Natural Language and Sketching [[paper]](https://arxiv.org/abs/2403.17693) [[code]](https://github.com/fesiib/video-editing-pipeline) [[project page]](https://expressedit.kixlab.org/)\n- `[UIST 2023]` Automated Conversion of Music Videos into Lyric Videos [[paper]](https://arxiv.org/abs/2308.14922) [[project page]](https://majiaju.io/lyric-video)\n- `[NeurIPS 2022 Workshop]` VideoMap: Video Editing in Latent Space [[paper]](https://arxiv.org/abs/2211.12492) [[project page]](https://chuanenlin.com/videomap)\n- `[ECCV 2022]` AutoTransition: Learning to Recommend Video Transition Effects [[paper]](https://arxiv.org/abs/2207.13479) [[code]](https://github.com/acherstyx/AutoTransition) [[dataset]](https://drive.google.com/file/d/179r-bRu9trSgqh4ejhyplfFKO2ta98BT/view?usp=sharing)\n- `[IJCAI 2020 Demonstrations Track]` An AI-Empowered Visual Storyline Generator [[paper]](https://dl.acm.org/doi/abs/10.5555/3491440.3492205) 🛒\n- `[AAAI 2020 Student Abstract]` Generating Engaging Promotional Videos for E-commerce Platforms [[paper]](https://ojs.aaai.org/index.php/AAAI/article/view/7205) 🛒\n- `[UIST 2020]` Automatic Video Creation From a Web Page [[paper]](https://dl.acm.org/doi/abs/10.1145/3379337.3415814)\n- `[TOM 2020]` AutoFoley: Artificial Synthesis of Synchronized Sound Tracks for Silent Videos With Deep Learning [[paper]](https://arxiv.org/abs/2002.10981)\n- `[CHI 2019]` B-Script: Transcript-based B-roll Video Editing with Recommendations [[paper]](https://dl.acm.org/doi/pdf/10.1145/3290605.3300311)\n### Fast-Forwarding \u0026 Retiming\n**To change the video speed.**\n- `[PRL 2023]` A Multimodal Hyperlapse Method Based on Video and Songs' Emotion Alignment [[paper]](https://www.sciencedirect.com/science/article/abs/pii/S0167865522002537)\n- `[TPAMI 2023]` Text-Driven Video Acceleration: A Weakly-Supervised Reinforcement Learning Method [[paper]](https://arxiv.org/abs/2203.15778) [[project page]](https://www.verlab.dcc.ufmg.br/semantic-hyperlapse/tpami2022/)\n- `[CVPR 2022 Workshop]` Video-ReTime: Learning Temporally Varying Speediness for Time Remapping [[paper]](https://arxiv.org/abs/2205.05609)\n- `[TPAMI 2020]` A Sparse Sampling-Based Framework for Semantic Fast-Forward of First-Person Videos [[paper]](https://arxiv.org/abs/2009.11063)\n- `[MM 2020]` Automated Aesthetic Enhancement of Videos [[paper]](https://dl.acm.org/doi/abs/10.1145/1873951.1873991) 💃\n- `[CVPR 2018]` A Weighted Sparse Sampling and Smoothing Frame Transition Approach for Semantic Fast-Forward First-Person Videos [[paper]](https://arxiv.org/abs/1802.08722) [[project page]](https://www.verlab.dcc.ufmg.br/semantic-hyperlapse/)\n- `[ECCV 2016 Workshop]` Towards Semantic Fast-Forward and Stabilized Egocentric Videos [[paper]](https://arxiv.org/abs/1708.04146)\n- `[ICIP 2016]` Fast-Forward Video Based on Semantic Extraction [[paper]](https://arxiv.org/abs/1708.04160)\n- `[TOG 2015]` Real-Time Hyperlapse Creation via Optimal Frame Selection [[paper]](https://dl.acm.org/doi/abs/10.1145/2766954)\n- `[TOG 2014]` First-Person Hyper-Lapse Videos [[paper]](https://dl.acm.org/doi/abs/10.1145/2601097.2601195)\n### Music-Driven Editing\n- `[arxiv 2023]` AutoMatch: A Large-scale Audio Beat Matching Benchmark for Boosting Deep Learning Assistant Video Editing [[paper]](https://arxiv.org/abs/2303.01884)\n- `[SIBGRAPI 2021]` Musical Hyperlapse: A Multimodal Approach to Accelerate First-Person Videos [[paper]](https://www.computer.org/csdl/proceedings-article/sibgrapi/2021/235400a184/1zurthy1oJ2)\n- `[CVPR 2018 Workshop]` Visual Rhythm and Beat [[paper]](https://openaccess.thecvf.com/content_cvpr_2018_workshops/w49/html/Davis_Visual_Rhythm_and_CVPR_2018_paper.html)\n- `[TOG 2015]` audeosynth: Music-Driven Video Montage [[paper]](https://dl.acm.org/doi/abs/10.1145/2766966)\n### Spatial Editing\n**To crop the video based on actionness, aesthetics, etc.**\n- `[arxiv 2024]` Reframe Anything: LLM Agent for Open World Video Reframing [[paper]](https://arxiv.org/abs/2403.06070)\n- `[WACV 2024]` Real Time GAZED: Online Shot Selection and Editing of Virtual Cameras from Wide-Angle Monocular Video Recordings [[paper]](https://arxiv.org/abs/2311.15581)\n- `[CVPR 2020 Workshop]` As Seen on TV: Automatic Basketball Video Production Using Gaussian-Based Actionness and Game States Recognition [[paper]](https://openaccess.thecvf.com/content_CVPRW_2020/html/w53/Quiroga_As_Seen_on_TV_Automatic_Basketball_Video_Production_Using_Gaussian-Based_CVPRW_2020_paper.html) [[project page]]( https://gsbasketball.github.io) 🏀\n- `[CHI 2020]` GAZED– Gaze-guided Cinematic Editing of Wide-Angle Monocular Video Recordings [[paper]](https://dl.acm.org/doi/abs/10.1145/3313831.3376544) 💃\n- `[SA 2017 Poster]` Aesthetic Temporal and Spatial Editing of Casual Videos [[paper]](https://dl.acm.org/doi/abs/10.1145/3145690.3145733)\n### Video Editing Styles Transfer\n**To extract the editing styles in a source video and apply them to other video footages.**\n- `[CVPR 2023]` JAWS: Just A Wild Shot for Cinematic Transfer in Neural Radiance Fields [[paper]](https://arxiv.org/abs/2303.15427) [[project page]](https://www.lix.polytechnique.fr/vista/projects/2023_cvpr_wang/)\n- `[CVPR 2021 Workshop]` Editing Like Humans: A Contextual, Multimodal Framework for Automated Video Editing [[paper]](https://openaccess.thecvf.com/content/CVPR2021W/MULA/html/Koorathota_Editing_Like_Humans_A_Contextual_Multimodal_Framework_for_Automated_Video_CVPRW_2021_paper.html) [[project page]](http://cmve.foveainsights.com/) 💬\n- `[CVPR 2021 Workshop]` Automatic Non-Linear Video Editing Transfer [[paper]](https://arxiv.org/abs/2105.06988)\n### Virtual Cinematography\n- `[CVPR 2024]` Cinematic Behavior Transfer via NeRF-based Differentiable Filming [[paper]](https://arxiv.org/abs/2311.17754) [[project page]](https://virtualfilmstudio.github.io/projects/cinetransfer)\n- `[SIGGRAPH 2023 Poster]` Dynamic Storyboard Generation in an Engine-based Virtual Environment for Video Production [[paper]](https://arxiv.org/abs/2301.12688) [[project page]](https://virtualfilmstudio.github.io/)\n- `[CHI 2021]` Virtual Camera Layout Generation using a Reference Video [[paper]](https://dl.acm.org/doi/abs/10.1145/3411764.3445437)\n- `[TOMCCAP 2018]` Thinking Like a Director: Film Editing Patterns for Virtual Cinematographic Storytelling [[paper]](https://dl.acm.org/doi/abs/10.1145/3241057)\n\u003cbr/\u003e\n\n## Datasets And More\n**Datasets and papers related to video editing, camera movement🎥, shot type🖼️, etc.**\n- `[CVPR 2025]` VEU-Bench: Towards Comprehensive Understanding of Video Editing [[paper]](https://arxiv.org/abs/2504.17828) [[project page]](https://labazh.github.io/VEU-Bench.github.io/)\n- `[arxiv 2024]` Edit3K: Universal Representation Learning for Video Editing Components [[paper]](https://arxiv.org/abs/2403.16048) [[code]](https://github.com/GX77/Edit3K) [[dataset]](https://huggingface.co/datasets/Gstar666/Edit3K)\n- `[CVPR 2024]` Neighbor Relations Matter in Video Scene Detection [[paper]](https://openaccess.thecvf.com/content/CVPR2024/papers/Tan_Neighbor_Relations_Matter_in_Video_Scene_Detection_CVPR_2024_paper.pdf) [[code]](https://github.com/ExMorgan-Alter/NeighborNet)\n- `[WACV 2024]` Movie Genre Classification by Language Augmentation and Shot Sampling [[paper]](https://arxiv.org/abs/2203.13281) [[code]](https://github.com/Zhongping-Zhang/Movie-CLIP) 🎬\n- `[IMXw 2023]` Recognition of Camera Angle and Camera Level in Movies from Single Frames [[paper]](https://dl.acm.org/doi/fullHtml/10.1145/3604321.3604334) [[project page]](https://cinescale.github.io/camera_al/) 🎬🖼️\n- `[ICCV 2023 Workshop]` LEMMS: Label Estimation of Multi-feature Movie Segments [[paper]](https://openaccess.thecvf.com/content/ICCV2023W/CVEU/html/Vacchetti_LEMMS_Label_Estimation_of_Multi-Feature_Movie_Segments_ICCVW_2023_paper.html) 🎬🖼️\n- `[ICCV 2023]` Long-range Multimodal Pretraining for Movie Understanding [[paper]](https://arxiv.org/abs/2308.09775) 🎬\n- `[ECCV 2022 Workshop]` Movie Lens: Discovering and Characterizing Editing Patterns in the Analysis of Short Movie Sequences [[paper]](https://dl.acm.org/doi/abs/10.1007/978-3-031-25069-9_42) 🎬\n- `[ECCV 2022]` The Anatomy of Video Editing: A Dataset and Benchmark Suite for AI-Assisted Video Editing [[paper]](http://arxiv.org/abs/2207.09812) [[code \u0026 dataset]](https://github.com/dawitmureja/AVE) 🎬🎥🖼️\n- `[ECCV 2022]` MovieCuts: A New Dataset and Benchmark for Cut Type Recognition [[paper]](https://arxiv.org/abs/2109.05569) [[code \u0026 dataset]](https://github.com/PardoAlejo/MovieCuts) 🎬\n- `[ICIP 2022]` HISTORIAN: A Large-Scale HISTORIcal Film Dataset with Cinematographic ANnotation [[paper]](https://x.sci-hub.org.cn/target?link=https://www.vhh-project.eu/wp-content/uploads/VHH_Publication_HELM-Daniel_Historian_2022.pdf) [[code \u0026 dataset]](https://github.com/dahe-cvl/historian_dataset) 🎬🎥\n- `[ICIS Fall 2021]` RO-TextCNN Based MUL-MOVE-Net for Camera Motion Classification [[paper]](https://ieeexplore.ieee.org/abstract/document/9627386) [[code \u0026 dataset]](https://github.com/YMediaLab/Auto-Montage) 🎥\n- `[ICCV 2021 Workshop]` High-Level Features for Movie Style Understanding [[paper]](https://hal.archives-ouvertes.fr/hal-03381587/) 🎬🎥\n- `[ECCV 2020]` MovieNet: A Holistic Dataset for Movie Understanding [[paper]](https://arxiv.org/pdf/2007.10937.pdf) [[code]](https://github.com/movienet) [[project page \u0026 dataset]](https://movienet.github.io/) 🎬🎥🖼️\n- `[ECCV 2020]` A Unified Framework for Shot Type Classification Based on Subject Centric Lens [[paper]](http://arxiv.org/abs/2008.03548) [[project page \u0026 dataset]](https://anyirao.com/projects/ShotType.html) 🎬🎥🖼️\n- `[ICIP 2011]` Using Context Saliency For Movie Shot Classification [[paper]](http://www.nlpr.ia.ac.cn/2011papers/gjhy/gh121.pdf) 🎬🖼️\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwentianli%2Fawesome-video-editing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwentianli%2Fawesome-video-editing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwentianli%2Fawesome-video-editing/lists"}