{"url":"/dataset/kit-motion-language","name":"KIT Motion-Language","full_name":null,"description_markdown":"The KIT Motion-Language is a dataset linking human motion and natural language.\r\n\r\nSource: [The KIT Motion-Language Dataset](/paper/the-kit-motion-language-dataset)","description_withheld":null,"homepage":"https://gitlab.com/h2t/MotionAnnotation","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/the-kit-motion-language-dataset","title":"The KIT Motion-Language Dataset","first_author":"Matthias Plappert","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Actions","url":"/datasets/modality/actions"}],"tasks":[{"name":"Feature Engineering","url":"/task/feature-engineering","datasets_with_task":"/datasets/task/feature-engineering"},{"name":"Motion Synthesis","url":"/task/motion-synthesis","datasets_with_task":"/datasets/task/motion-synthesis"},{"name":"Motion Captioning","url":"/task/motion-captioning","datasets_with_task":"/datasets/task/motion-captioning"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["KIT Motion-Language"],"data_loaders":[{"repo":"https://gitlab.com/h2t/MotionAnnotation","url":"https://gitlab.com/h2t/MotionAnnotation","frameworks":[]}],"num_papers_in_archive":48,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/motion-synthesis-on-kit-motion-language","task":"Motion Synthesis","dataset_variant":"KIT Motion-Language","rows":31,"metrics":["FID","R Precision Top3","Diversity","Multimodality"],"first_row_in_archive_order":{"model":"Motion Anything","paper":"/paper/motion-anything-any-to-motion-generation","metrics":{"Diversity":"10.94","FID":"0.131","Multimodality":"1.374","R Precision Top3":"0.802"},"code_links":[{"title":"steve-zeyu-zhang/MotionAnything","url":"https://github.com/steve-zeyu-zhang/MotionAnything"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/motion-captioning-on-kit-motion-language","task":"Motion Captioning","dataset_variant":"KIT Motion-Language","rows":3,"metrics":["BLEU-4","BERTScore"],"first_row_in_archive_order":{"model":"MLP+GRU","paper":"/paper/motion2language-unsupervised-learning-of","metrics":{"BERTScore":"42.1","BLEU-4":"25.4"},"code_links":[{"title":"rd20karim/M2T-Segmentation","url":"https://github.com/rd20karim/M2T-Segmentation"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/motion-anything-any-to-motion-generation","title":"Motion Anything: Any to Motion Generation","date":"2025-03-10","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/motionpcm-real-time-motion-synthesis-with","title":"MotionPCM: Real-Time Motion Synthesis with Phased Consistency Model","date":"2025-01-31","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/free-t2m-frequency-enhanced-text-to-motion","title":"Free-T2M: Frequency Enhanced Text-to-Motion Diffusion Model With Consistency Loss","date":"2025-01-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/discord-discrete-tokens-to-continuous-motion","title":"DisCoRD: Discrete Tokens to Continuous Motion via Rectified Flow Decoding","date":"2024-11-29","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/bipo-bidirectional-partial-occlusion-network-1","title":"BiPO: Bidirectional Partial Occlusion Network for Text-to-Motion Synthesis","date":"2024-11-28","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/bad-bidirectional-auto-regressive-diffusion","title":"BAD: Bidirectional Auto-regressive Diffusion for Text-to-Motion Generation","date":"2024-09-17","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/bamm-bidirectional-autoregressive-motion","title":"BAMM: Bidirectional Autoregressive Motion Model","date":"2024-03-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/parco-part-coordinating-text-to-motion","title":"ParCo: Part-Coordinating Text-to-Motion Synthesis","date":"2024-03-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/motion-mamba-efficient-and-long-sequence","title":"Motion Mamba: Efficient and Long Sequence Motion Generation","date":"2024-03-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/guess-gradually-enriching-synthesis-for-text","title":"GUESS:GradUally Enriching SyntheSis for Text-Driven Human Motion Generation","date":"2024-01-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/finemogen-fine-grained-spatio-temporal-motion-1","title":"FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing","date":"2023-12-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/mmm-generative-masked-motion-model","title":"MMM: Generative Masked Motion Model","date":"2023-12-06","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/emdm-efficient-motion-diffusion-model-for","title":"EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation","date":"2023-12-04","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":7,"samples_ran":3,"samples_unverified":4,"pointer_only_for_licence":7,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/momask-generative-masked-modeling-of-3d-human","title":"MoMask: Generative Masked Modeling of 3D Human Motions","date":"2023-11-29","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":11,"samples_ran":8,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/motion2language-unsupervised-learning-of","title":"Motion2Language, unsupervised learning of synchronized semantic motion segmentation","date":"2023-10-16","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/guided-attention-for-interpretable-motion","title":"Guided Attention for Interpretable Motion Captioning","date":"2023-10-11","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/act-as-you-wish-fine-grained-control-of","title":"Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs","date":"2023-09-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/fg-t2m-fine-grained-text-driven-human-motion","title":"Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model","date":"2023-09-12","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/diversemotion-towards-diverse-human-motion","title":"DiverseMotion: Towards Diverse Human Motion Generation via Discrete Diffusion","date":"2023-09-04","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/attt2m-text-driven-human-motion-generation-1","title":"AttT2M: Text-Driven Human Motion Generation with Multi-Perspective Attention Mechanism","date":"2023-09-02","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/remodiffuse-retrieval-augmented-motion","title":"ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model","date":"2023-04-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/t2m-gpt-generating-human-motion-from-textual","title":"T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations","date":"2023-01-15","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":7,"samples_ran":5,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/executing-your-commands-via-motion-diffusion","title":"Executing your Commands via Motion Diffusion in Latent Space","date":"2022-12-08","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/human-motion-diffusion-model","title":"Human Motion Diffusion Model","date":"2022-09-29","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/motiondiffuse-text-driven-human-motion","title":"MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model","date":"2022-08-31","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/tm2t-stochastic-and-tokenized-modeling-for","title":"TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts","date":"2022-07-04","rows_on_this_dataset":4,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":7,"samples_ran":5,"samples_unverified":2,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/generating-diverse-and-natural-3d-human","title":"Generating Diverse and Natural 3D Human Motions From Text","date":"2022-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":9,"samples_harvested":39,"samples_ran":28,"samples_unverified":11,"pointer_only_for_licence":13,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}