{"url":"/dataset/eth","name":"ETH","full_name":"ETH Pedestrian","description_markdown":"**ETH** is a dataset for pedestrian detection. The testing set contains 1,804 images in three video clips. The dataset is captured from a stereo rig mounted on car, with a resolution of 640 x 480 (bayered), and a framerate of 13--14 FPS.\r\n\r\nSource: [Scale-aware Fast R-CNN for Pedestrian Detection](https://arxiv.org/abs/1510.08160)\r\nImage Source: [https://medium.com/@zhenqinghu/pedestrian-detection-on-eth-data-set-with-faster-r-cnn-19d0a906f1d3](https://medium.com/@zhenqinghu/pedestrian-detection-on-eth-data-set-with-faster-r-cnn-19d0a906f1d3)","description_withheld":null,"homepage":"https://data.vision.ee.ethz.ch/cvl/aess/dataset/","introduced_date":"2007-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Depth and Appearance for Mobile Scene Analysis","first_author":null,"url":"https://doi.org/10.1109/ICCV.2007.4409092"},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Person Re-Identification","url":"/task/person-re-identification","datasets_with_task":"/datasets/task/person-re-identification"},{"name":"Trajectory Prediction","url":"/task/trajectory-prediction","datasets_with_task":"/datasets/task/trajectory-prediction"},{"name":"Pedestrian Detection","url":"/task/pedestrian-detection","datasets_with_task":"/datasets/task/pedestrian-detection"},{"name":"Multi-future Trajectory Prediction","url":"/task/multi-future-trajectory-prediction","datasets_with_task":"/datasets/task/multi-future-trajectory-prediction"},{"name":"Multi Future Trajectory Prediction","url":"/task/multi-future-trajectory-prediction-1","datasets_with_task":"/datasets/task/multi-future-trajectory-prediction-1"}],"languages":[],"variants":["ETH BIWI Walking Pedestrians dataset","ETH/UCY","ETH"],"data_loaders":[{"repo":"https://github.com/shayswrld/eth_pedestrian_loader","url":"https://github.com/shayswrld/eth_pedestrian_loader","frameworks":["tf","pytorch","jax"]}],"num_papers_in_archive":58,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/trajectory-prediction-on-ethucy","task":"Trajectory Prediction","dataset_variant":"ETH/UCY","rows":20,"metrics":["ADE-8/12","FDE-8/12"],"first_row_in_archive_order":{"model":"NSP","paper":"/paper/human-trajectory-prediction-via-neural-social","metrics":{"ADE-8/12":"0.17","FDE-8/12":"0.24"},"code_links":[{"title":"realcrane/human-trajectory-prediction-via-neural-social-physics","url":"https://github.com/realcrane/human-trajectory-prediction-via-neural-social-physics"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/trajectory-prediction-on-eth","task":"Trajectory Prediction","dataset_variant":"ETH","rows":5,"metrics":["Avg AMD/AMV 8/12"],"first_row_in_archive_order":{"model":"Social-Implicit","paper":"/paper/social-implicit-rethinking-trajectory","metrics":{"Avg AMD/AMV 8/12":"0.90"},"code_links":[{"title":"abduallahmohamed/social-implicit","url":"https://github.com/abduallahmohamed/social-implicit"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/trajectory-prediction-on-eth-biwi-walking","task":"Trajectory Prediction","dataset_variant":"ETH BIWI Walking Pedestrians dataset","rows":1,"metrics":["ADE-8/12"],"first_row_in_archive_order":{"model":"Social Ways","paper":"/paper/social-ways-learning-multi-modal","metrics":{"ADE-8/12":"0.39"},"code_links":[{"title":"amiryanj/socialways","url":"https://github.com/amiryanj/socialways"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/progressive-pretext-task-learning-for-human","title":"Progressive Pretext Task Learning for Human Trajectory Prediction","date":"2024-07-16","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":4,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/eqmotion-equivariant-multi-agent-motion","title":"EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning","date":"2023-03-20","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/human-trajectory-prediction-via-neural-social","title":"Human Trajectory Prediction via Neural Social Physics","date":"2022-07-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":3,"samples_unverified":3,"pointer_only_for_licence":6,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/remember-intentions-retrospective-memory","title":"Remember Intentions: Retrospective-Memory-based Trajectory Prediction","date":"2022-03-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/social-implicit-rethinking-trajectory","title":"Social-Implicit: Rethinking Trajectory Prediction Evaluation and The Effectiveness of Implicit Maximum Likelihood Estimation","date":"2022-03-06","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":0,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/view-vertically-a-hierarchical-network-for","title":"View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums","date":"2021-10-14","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/stepwise-goal-driven-networks-for-trajectory","title":"Stepwise Goal-Driven Networks for Trajectory Prediction","date":"2021-03-25","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/agentformer-agent-aware-transformers-for","title":"AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting","date":"2021-03-25","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":17,"samples_ran":4,"samples_unverified":13,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/where-are-you-heading-dynamic-trajectory","title":"Where Are You Heading? Dynamic Trajectory Prediction With Expert Goal Examples","date":"2021-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/social-nce-contrastive-learning-of-socially","title":"Social NCE: Contrastive Learning of Socially-aware Motion Representations","date":"2020-12-21","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+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/temporal-pyramid-network-for-pedestrian","title":"Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision","date":"2020-12-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/from-goals-waypoints-paths-to-long-term-human","title":"From Goals, Waypoints & Paths To Long Term Human Trajectory Forecasting","date":"2020-12-02","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/mantra-memory-augmented-networks-for-multiple-1","title":"MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction","date":"2020-06-05","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/it-is-not-the-journey-but-the-destination","title":"It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction","date":"2020-04-04","rows_on_this_dataset":1,"code_links":4,"syntology":null},{"paper":"/paper/transformer-networks-for-trajectory","title":"Transformer Networks for Trajectory Forecasting","date":"2020-03-18","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/social-stgcnn-a-social-spatio-temporal-graph","title":"Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction","date":"2020-02-27","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/trajectron-multi-agent-generative-trajectory","title":"Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data","date":"2020-01-09","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":4,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/social-bigat-multimodal-trajectory","title":"Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks","date":"2019-07-04","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/conditional-generative-neural-system-for","title":"Conditional Generative Neural System for Probabilistic Trajectory Prediction","date":"2019-05-05","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/social-ways-learning-multi-modal","title":"Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs","date":"2019-04-20","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/peeking-into-the-future-predicting-future","title":"Peeking into the Future: Predicting Future Person Activities and Locations in Videos","date":"2019-02-11","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":27,"samples_ran":2,"samples_unverified":25,"pointer_only_for_licence":22,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/sophie-an-attentive-gan-for-predicting-paths","title":"SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints","date":"2018-06-05","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+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/social-gan-socially-acceptable-trajectories","title":"Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks","date":"2018-03-29","rows_on_this_dataset":1,"code_links":8,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":4,"samples_unverified":6,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":12,"samples_harvested":100,"samples_ran":28,"samples_unverified":72,"pointer_only_for_licence":38,"papers_with_no_sample_that_ran":3,"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."}