[ { "Top-1 (%)": 34.27, "Top-5 (%)": 62.71, "code_links": [], "date": "2019-05-30", "date2": 20190530, "model": "AssembleNet", "paper": { "title": "AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures", "url": "https://cknow.io/lib/744574884b3457d2" }, "paper_data_uoa": "744574884b3457d2" }, { "Top-1 (%)": 31.16, "Top-5 (%)": 57.67, "code_links": [ { "title": "zhoubolei/moments_models", "url": "https://github.com/zhoubolei/moments_models" }, { "title": "metalbubble/moments_models", "url": "https://github.com/metalbubble/moments_models" }, { "title": "thefonseca/predictive-coding", "url": "https://github.com/thefonseca/predictive-coding" }, { "title": "shubhambitsg/activity-recognition", "url": "https://github.com/shubhambitsg/activity-recognition" } ], "date": "2018-01-09", "date2": 20180109, "model": "Ensemble (SVM)", "paper": { "title": "Moments in Time Dataset: one million videos for event understanding", "url": "https://cknow.io/lib/1224a44775a4689b" }, "paper_data_uoa": "1224a44775a4689b" }, { "Top-1 (%)": 29.51, "Top-5 (%)": 56.06, "code_links": [ { "title": "zhoubolei/moments_models", "url": "https://github.com/zhoubolei/moments_models" }, { "title": "metalbubble/moments_models", "url": "https://github.com/metalbubble/moments_models" }, { "title": "thefonseca/predictive-coding", "url": "https://github.com/thefonseca/predictive-coding" }, { "title": "shubhambitsg/activity-recognition", "url": "https://github.com/shubhambitsg/activity-recognition" } ], "date": "2018-01-09", "date2": 20180109, "model": "I3D", "paper": { "title": "Moments in Time Dataset: one million videos for event understanding", "url": "https://cknow.io/lib/1224a44775a4689b" }, "paper_data_uoa": "1224a44775a4689b" }, { "Top-1 (%)": 28.27, "Top-5 (%)": 53.87, "code_links": [ { "title": "zhoubolei/moments_models", "url": "https://github.com/zhoubolei/moments_models" }, { "title": "metalbubble/moments_models", "url": "https://github.com/metalbubble/moments_models" }, { "title": "thefonseca/predictive-coding", "url": "https://github.com/thefonseca/predictive-coding" }, { "title": "shubhambitsg/activity-recognition", "url": "https://github.com/shubhambitsg/activity-recognition" } ], "date": "2018-01-09", "date2": 20180109, "model": "TRN-Multiscale", "paper": { "title": "Moments in Time Dataset: one million videos for event understanding", "url": "https://cknow.io/lib/1224a44775a4689b" }, "paper_data_uoa": "1224a44775a4689b" }, { "Top-1 (%)": 15.71, "Top-5 (%)": 34.65, "code_links": [ { "title": "zhoubolei/moments_models", "url": "https://github.com/zhoubolei/moments_models" }, { "title": "metalbubble/moments_models", "url": "https://github.com/metalbubble/moments_models" }, { "title": "thefonseca/predictive-coding", "url": "https://github.com/thefonseca/predictive-coding" }, { "title": "shubhambitsg/activity-recognition", "url": "https://github.com/shubhambitsg/activity-recognition" } ], "date": "2018-01-09", "date2": 20180109, "model": "TSN-Flow", "paper": { "title": "Moments in Time Dataset: one million videos for event understanding", "url": "https://cknow.io/lib/1224a44775a4689b" }, "paper_data_uoa": "1224a44775a4689b" }, { "Top-1 (%)": 7.6, "Top-5 (%)": 18, "code_links": [ { "title": "zhoubolei/moments_models", "url": "https://github.com/zhoubolei/moments_models" }, { "title": "metalbubble/moments_models", "url": "https://github.com/metalbubble/moments_models" }, { "title": "thefonseca/predictive-coding", "url": "https://github.com/thefonseca/predictive-coding" }, { "title": "shubhambitsg/activity-recognition", "url": "https://github.com/shubhambitsg/activity-recognition" } ], "date": "2018-01-09", "date2": 20180109, "model": "SoundNet", "paper": { "title": "Moments in Time Dataset: one million videos for event understanding", "url": "https://cknow.io/lib/1224a44775a4689b" }, "paper_data_uoa": "1224a44775a4689b" } ]