Kinetics-600 Papers With Code is a free resource with all data licensed under CC-BY-SA. All the videos are collected from YouTube and have a fixed Kinetics-400 UniFormerV2-L (ViT-L, 336) FLOPs (G) x views Papers With Code is a free resource with all data licensed under CC-BY-SA. For the other 32 classes, we renamed a few (e. 1 top-1 accuracy on Kinetics-600 with ~20x less pre-training data and ~3x smaller model size) and temporal modeling (69. We conduct thorough ablation studies, and achieve state-of-the-art results on multiple video classification benchmarks including Kinetics 400 and 600, Epic Kitchens, Something-Something v2 and Moments in Time, outperforming prior methods based on deep 3D convolutional networks. Kinetics has two orders of magnitude more data, with 400 Nov 27, 2023 · Kinetics-400 Side4Video (EVA, ViT-E/14) Acc@1 Papers With Code is a free resource with all data licensed under CC-BY-SA. 0 [10]) Acc@5 Papers With Code is a free resource with all data licensed under CC-BY-SA. In this new version, there are at least 700 video clips from different YouTube videos for each of the 700 classes. 58M action labels with multiple labels per person occurring frequently. 8% absolute) on Kinetics-400 compared to the baseline training method. 0 RefCOCO ESC-50 AudioCaps VGG-Sound Clotho FSD50K Google Refexp AVQA Mar 11, 2024 · ImageNet Kinetics Kinetics 400 MSR-VTT MSVD DiDeMo Breakfast COIN Results from the Paper Papers With Code is a free resource with all data licensed under CC-BY-SA. See a full comparison of 3 papers with code. 6 top-1 accuracy on Something-Something v2). The dataset contains 400 human action classes, with at least 400 video clips for each action. This paper re-evaluates state-of-the-art architectures in light of the new Kinetics Human Action Video dataset. Humans perceive the world by concurrently processing and fusing high-dimensional inputs from multiple modalities such as vision and audio. May 4, 2022 · ImageNet MS COCO Kinetics Flickr30k Kinetics 400 MSR-VTT ImageNet-R Visual Question Answering v2. Kinetics Kinetics 400 Charades Something-Something V2 Kinetics-600 Kinetics-700 JFT-3B Results from the Paper Edit Kinetics-700 is a video dataset of 650,000 clips that covers 700 human action classes. Oct 21, 2020 · We describe the 2020 edition of the DeepMind Kinetics human action dataset, which replenishes and extends the Kinetics-700 dataset. May 19, 2017 · The dataset contains 400 human action classes, with at least 400 video clips for each action. #109 best model for Action Classification on Kinetics-400 (Acc@1 metric) Browse State-of-the-Art Stay informed on the latest trending ML papers with code This paper introduces a video dataset of spatio-temporally localized Atomic Visual Actions (AVA). The actions are human focussed and cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions Mar 9, 2024 · The original module was trained on the kinetics-400 dateset and knows about 400 different actions. The goal of skeleton-based action recognition is to develop algorithms that can understand and classify human actions from skeleton data, which can be used in The current state-of-the-art on Kinetics-400 is InternVideo-T. The current state-of-the-art on Kinetics-400 is SVT. In this Colab we will use it recognize activities in videos from a UCF101 dataset. Each clip lasts around 10s and is taken from a different YouTube video. Papers With Code is a free resource with all The current state-of-the-art on Kinetics-400 is OmniVec2. See a full comparison of 194 papers with code. This paper details the changes introduced for this new release of the dataset, and includes a comprehensive set of statistics as well as baseline results using the I3D neural network architecture. See a full comparison of 41 papers with code. Our proposed improvements address all three main components of a ResNet: the flow of information through the network layers, the residual 3. Residual networks (ResNets) represent a powerful type of convolutional neural network (CNN) architecture, widely adopted and used in various tasks. 143 datasets • 116140 papers with code. ImageNet UCF101 Kinetics HMDB51 Kinetics 400 THUMOS14 Something-Something V2 WebVid Kinetics-600 Something-Something V1 AVA JFT-3B FineAction Results from the Paper Edit The current state-of-the-art on Kinetics-400 is OmniVec2. May 31, 2021 · This is validated with multiple models on Kinetics-400 and Charades with remarkable results: CoX3D models attain state-of-the-art complexity/accuracy trade-offs on Kinetics-400 with 12. Machine perception models, in stark contrast, are typically modality-specific and optimised for unimodal benchmarks, and hence late-stage fusion of final representations or predictions from each modality (`late-fusion') is still a dominant paradigm for Jul 1, 2021 · 🏆 SOTA for Boundary Detection on Kinetics-400 (Pairwise F1 metric) Browse State-of-the-Art Papers With Code is a free resource with all data licensed under CC Kinetics Kinetics 400 Charades Something-Something V2 EPIC-KITCHENS-100 Kinetics-600 MiT Kinetics-700 Results from the Paper Edit Contribute to Tramac/tiny-kinetics-400 development by creating an account on GitHub. The current state-of-the-art on Kinetics-400 is InternVideo2-6B. The AVA dataset densely annotates 80 atomic visual actions in 430 15-minute video clips, where actions are localized in space and time, resulting in 1. In order to scale up the dataset we changed the data collection process so it uses multiple queries per class, with some of them in a language other than english -- portuguese. Kinetics-GEB+ (Generic Event Boundary Captioning, Grounding and Retrieval) is a dataset that consists of over 170k boundaries associated with captions describing status changes in the generic events in 12K videos. It was created to address the unique challenges associated with recognizing videos See full list on github. See a full comparison of 199 papers with code. Our motivation stems from the observation that 2D CNNs applied to individual frames of the video have remained solid performers in action recognition. 5 and 84. 3%. SlowFast (Kinetics-400 pretraining) mAP (Val) 26. com Kinetics-400 Video-SwinV2-G (ImageNet-22k and external 70M pretrain) Papers With Code is a free resource with all data licensed under CC-BY-SA. See a full comparison of 4 papers with code. 8% improvements in accuracy compared to regular X3D models while reducing peak memory consumption by up to 48%. 0 on Kinetics-400 and 83. This paper details the changes between the Jul 25, 2024 · UCF101 Kinetics Kinetics 400 Something-Something V2 Animal Kingdom Papers With Code is a free resource with all data licensed under CC-BY-SA. Kinetics-400 irCSN-152 (IG-Kinetics-65M pretrain) Acc@1 Papers With Code is a free resource with all data licensed under CC-BY-SA. Nov 30, 2023 · We validate the proposed method with extensive experiments on public benchmarks with different characteristics: EPIC-KITCHENS-100, Something-Something-V2, and Kinetics-400. Kinetics 400. ImageNet Kinetics Kinetics 400 Charades Something-Something V2 Kinetics-600 AVA Results from the Paper Edit Jan 23, 2023 · View a PDF of the paper titled Zorro: the masked multimodal transformer, by Adri\`a Recasens and 10 other authors View PDF Abstract: Attention-based models are appealing for multimodal processing because inputs from multiple modalities can be concatenated and fed to a single backbone network - thus requiring very little fusion engineering. Each clip is annotated with an action class and lasts approximately 10 seconds. Kinetics-400 TAdaConvNeXt-T Acc@1 Papers With Code is a free resource with all data licensed under CC-BY-SA. However, they rely on a huge image dataset In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition. Kinetics-400 RepFlow-50 ([2+1]D CNN, FcF, Non-local block) Acc@1 Papers With Code is a free resource with all data licensed under CC-BY-SA. Nov 25, 2019 · To learn more about the dataset, including how it was curated, be sure to refer to Kay et al. Newsletter RC2022. Nov 30, 2023 · Upload an image to customize your repository’s social media preview. The PortraitMode-400 dataset is a significant contribution to the field of video recognition, specifically focusing on portrait mode videos. The current state-of-the-art on Kinetics-Skeleton dataset is Structured Keypoint Pooling (PPNv2 skeletons+objects). Jun 13, 2023 · This is a subset of Kinetics-400, introduced in Look, Listen and Learn by Relja Arandjelovic and Andrew Zisserman. on videos). 57. Aug 3, 2018 · We describe an extension of the DeepMind Kinetics human action dataset from 400 classes, each with at least 400 video clips, to 600 classes, each with at least 600 video clips. Notably, our VideoMAE with the vanilla ViT can achieve 87. Kinetics-400 InternVideo-T See all. Prepare the Kinetics400 dataset¶. Our method consistently shows favorable performance across these datasets, while the performance of existing methods fluctuates depending on the dataset characteristics. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands. In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in The current state-of-the-art on Kinetics-400 is CVRL (R3D-152 2x; K600 pretrain). 5 41 Billion 2017 Papers With Code is a free resource with all data licensed under CC-BY-SA. 8 on Kinetics-600 without pre-training. The 480K videos are divided into 390K, 30K, 60K for training, validation and test sets, respectively. See a full comparison of 1 papers with code. This paper presents X3D, a family of efficient video networks that progressively expand a tiny 2D image classification architecture along multiple network axes, in space, time, width and depth. 4%, Kinetics-600 by 2. Kinetics 400 NTU RGB+D JHMDB Papers With Code is a free resource with all data licensed under CC-BY-SA. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes. 3 Papers With Code is a free resource with all data licensed under CC-BY-SA. See a full comparison of 36 papers with code. Feb 26, 2019 · **Action Recognition** is a computer vision task that involves recognizing human actions in videos or images. The goal of skeleton-based action recognition is to develop algorithms that can understand and classify human actions from skeleton data, which can be used in The current state-of-the-art on MiniKinetics is MARS+RGB+Flow (16 frames). In this repository, we provide PyTorch code for training and testing our proposed TimeSformer model. 3% on UCF101, and 62. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions such as 8 code implementations in TensorFlow and PyTorch. Since these works, numerous vision Transformer variants have been proposed to improve the accuracy at relatively small scale [14,21,34,42,63,68,71,75,77,78,82]. UCF101 dataset is an extension of UCF50 and consists of 13,320 video clips, which are classified into 101 categories. Imbalanced-MiniKinetics200 was proposed by "Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition" to evaluate varying scenarios of video long-tailed recognition Similar to CIFAR-10/100-LT, it utilizes an imbalance factor to construct long-tailed variants of the MiniKinetics200 dataset. The Kinetics-600 is a large-scale action recognition dataset which consists of around 480K videos from 600 action categories. Kinetics-400 MViT-B (train from scratch) Mar 23, 2022 · Kinetics-400 VideoMAE (no extra data, ViT-L, 16x4) Acc@1 Papers With Code is a free resource with all data licensed under CC-BY-SA. Each action class has at least 700 video clips. Without bells-and-whistles, MViTv2 has state-of-the-art performance in 3 domains: 88. Browse State-of-the-Art Datasets ; Methods; More . The current state-of-the-art on Kinetics-400 is CASTANET+ Ensemble. Feb 14, 2020 · If you are interested in performing deep learning for human activity or action recognition, you are bound to come across the Kinetics dataset released by deep mind. TSM is featured by MIT News / MIT Technology Review / WIRED / Engadget / NVIDIA News (09/2020) We update the environment setup for the online_demo, and should be much easier to set up. e. Kinetics-400 CVRL (R3D-50) Top-1 accuracy % Papers With Code is a free resource with all data licensed under CC-BY-SA. 7 boxAP on COCO object detection as well as 86. Kinetics-400. Labels for these actions can be found in the label map file . When pre-trained on a large Web Video Text dataset, our best model achieves 83. Dec 14, 2021 · We term this approach as Co-training Videos and Images for Action Recognition (CoVeR). 6% on HMDB51, without using any The current state-of-the-art on Kinetics-400 is CAST-B/16. 3D ResNet for Human Activity Recognition Figure 2: Deep neural network advances on image classification with ImageNet have also led to success in deep learning activity recognition (i. “dy-ing hair” became “dyeing hair”), split or removed others The Kinetics-600 is a large-scale action recognition dataset which consists of around 480K videos from 600 action categories. In order to scale up the dataset we changed the data collection process so it uses multiple queries per class, with some of them in a language other than english **Skeleton-based Action Recognition** is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data captured from sensors such as Microsoft Kinect, Intel RealSense, and wearable devices. ImageNet MS COCO Visual Question Answering Kinetics Visual Genome ADE20K ImageNet-1K Flickr30k Kinetics 400 Visual Question Answering v2. May 22, 2017 · The paucity of videos in current action classification datasets (UCF-101 and HMDB-51) has made it difficult to identify good video architectures, as most methods obtain similar performance on existing small-scale benchmarks. py. There are 3 main versions of the dataset; Kinetics 400, Kinetics 600 and the Kinetics 700 version. The total length of these video clips is over 27 hours. The videos are collected from YouTube. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions such as Feb 1, 2021 · Kinetics-400 ViT-B-VTN+ ImageNet-21K (84. Code is available online. 81 # 1: Kinetics-400 : Papers With Code is a free resource with all data licensed under CC-BY-SA. These 101 categories can be classified into 5 types (Body motion, Human-human interactions, Human-object interactions, Playing musical instruments and Sports). May 8, 2022 · Write better code with AI White papers, Ebooks, Webinars and links to the kinetics-400 topic page so that developers can more easily learn about it. the abundant unlabeled Kinetics-400 data while Kinetics-400 OmniVec2 See all. Kinetics-400 ip-CSN-152 (IG-65M pretraining) The current state-of-the-art on Kinetics-700 is InternVideo2-6B. In particular, when pretrained on ImageNet-21K based on the TimeSFormer architecture, CoVeR improves Kinetics-400 Top-1 Accuracy by 2. See a full comparison of 200 papers with code. See a full comparison of 6 papers with code. View paper • Download dataset. Kinetics 600. The Kinetics dataset is a large-scale, high-quality dataset for human action recognition in videos. 3 on Kinetics-400 and Kinetics-600. We describe an extension of the DeepMind Kinetics human action dataset from 400 classes, each with at least 400 video clips, to 600 classes, each with at least 600 video clips. 7387 datasets • 124148 papers with code. ImageNet UCF101 Kinetics HMDB51 Kinetics 400 Something-Something V1 Results from the Paper Edit The current state-of-the-art on Kinetics-400 is STGAT. Oct 1, 2019 · Kinetics Kinetics 400 Results from the Paper Edit Papers With Code is a free resource with all data licensed under CC-BY-SA. Each video in the dataset is a 10-second clip of action moment annotated from raw YouTube video. ’s 2017 paper, The Kinetics Human Action Video Dataset. 5 # 1: Clip acc@5: 78. 3x reductions of FLOPs and 2. This paper details the changes introduced for this new release of the dataset, and includes a comprehensive set of statistics as well as baseline results The current state-of-the-art on Kinetics-400 is OmniVec2. The dataset consists of around 500,000 video clips covering 600 human action classes with at least 600 video clips for each action class. Kinetics-400 : ResNet (2+1)D : Clip acc@1: 57. Kinetics 400 Charades THUMOS14 Papers With Code is a free resource with all data licensed under CC-BY-SA. Kinetics-400 UniFormer-B (ImageNet-1K) Acc@1 Papers With Code is a free resource with all data licensed under CC-BY-SA. With default flags, this builds the I3D two-stream model, loads pre-trained I3D checkpoints into the TensorFlow session, and then passes an example video through the model. It is an extensions of the Kinetics-400 dataset. **Skeleton-based Action Recognition** is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data captured from sensors such as Microsoft Kinect, Intel RealSense, and wearable devices. 8% accuracy on ImageNet classification, 58. Kinetics-400 Unmasked Teacher (ViT-L) FLOPs (G) x views Papers With Code is a free resource with all data licensed under CC-BY-SA. 4% on Kinetics-400, 75. With 306,245 short trimmed videos from 400 action categories, it is one of the largest and most widely used dataset in the research community for benchmarking state-of-the-art video action recognition models. Kinetics has two orders of magnitude more data, with 400 human action classes and over 400 clips per class, and is collected from realistic, challenging YouTube videos. The Label indicates what activity is performed by the humans. Jul 15, 2019 · We describe an extension of the DeepMind Kinetics human action dataset from 600 classes to 700 classes, where for each class there are at least 600 video clips from different YouTube videos. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging. 4% on Something-Something V2, 91. 1% on Kinetics-400 video classification. Apr 10, 2020 · 2 code implementations in TensorFlow and PyTorch. 5x faster (wall-clock time, same hardware) while also improving accuracy (+0. g. See a full comparison of 201 papers with code. 0 HowTo100M WebVid Kinetics-600 Results from the Paper Kinetics-400 video action classification benchmark [2], etc. Kinetics-700 is a video dataset of 650,000 clips that covers 700 human action classes. Write better code with AI White papers, Ebooks, Webinars Our approach achieves state-of-the-art accuracy on a broad range of video recognition benchmarks, including on action recognition (84. It contains train, test and validation in CSV and JSON format. From Kinetics-400 to Kinetics-600 Kinetics-600 is an approximate superset of Kinetics-400 – overall, 368 of the original 400 classes are exactly the same in Kinetics-600 (except they have more examples). 3-3. 9 top-1 accuracy on Kinetics-400 and 86. Images should be at least 640×320px (1280×640px for best display). 3%, and SomethingSomething-v2 by 2. The current state-of-the-art on Kinetics-400 is OmniVec2. Terms . Let me provide you with more details: Dataset Overview: The PortraitMode-400 (PM-400) dataset is the first of its kind and is dedicated to portrait mode video recognition. Each video clip lasts around 10 seconds and is labeled with a single action class. 1-15. S3D-G (ImageNet, Kinetics-400 pretrained) Papers With Code is a free resource with all data licensed under CC-BY-SA. The current state-of-the-art on Kinetics-400 is CVRL (R3D-101). 0 ImageNet-A ImageNet-Sketch COCO Captions NoCaps ObjectNet Kinetics-600 SNLI-VE Kinetics-700 NLVR JFT-3B The dataset contains 400 human action classes, with at least 400 video clips for each action. May 19, 2017 · We describe the DeepMind Kinetics human action video dataset. ImageNet MS COCO Kinetics Visual Genome Flickr30k Kinetics 400 AudioSet MSR-VTT EuroSAT Visual Question Answering v2. Inspired by feature selection methods in machine learning, a simple stepwise network expansion approach is employed that expands a single axis in each Jul 15, 2019 · We describe an extension of the DeepMind Kinetics human action dataset from 600 classes to 700 classes, where for each class there are at least 600 video clips from different YouTube videos. TimeSformer provides an efficient video classification framework that achieves state-of-the-art results on several video action recognition benchmarks such as Kinetics-400. Kinetics400 is an action recognition dataset of realistic action videos, collected from YouTube. PDF Abstract CVPR 2020 PDF CVPR 2020 Abstract Run the example code using $ python evaluate_sample. Sep 3, 2021 · The resulting models, termed 3D ResNet-RS, attain competitive performance of 81. Kinetics 700. Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. In this work we propose an improved version of ResNets. Only a few works have attempted to scale up the vision Transform-ers [17,56,80]. After downloading the dataset, extract the zip file. As an illustrative example, the proposed multigrid method trains a ResNet-50 SlowFast network 4. ww aw hb so rk lu dv le jw ga