WebWith only 25% computation increment, 7x7 kernels achieve +14.0 mAP better than 3x3 kernels on the CrowdPose dataset. On mobile platforms, LitePose reduces the latency by up to 5.0x without sacrificing performance, compared with prior state-of-the-art efficient pose estimation models, pushing the frontier of real-time multi-person pose ... WebApr 12, 2024 · Our approach uses a transformer to obtain context-aware embeddings for all detected keypoints and centers and then applies multi-head attention to directly group …

CrowdPose Benchmark (Multi-Person Pose Estimation) Papers …

WebDec 2, 2024 · In CrowdPose [37] and OCHuman [110], the occluded joints are manually labeled by annotators. The Syn-cOCC [111] dataset is a synthetic dataset generated by Un-realCV [67] so it provides accurate ... WebFeb 8, 2024 · For instance, it achieves 71.3% AP on CrowdPose in multi-person pose estimation, outperforming the recent single-stage DEKR by 5.6%, the bottom-up CenterAttention by 3.7%, and the top-down JC-SPPE by 5.3%. This advantage sustains on multi-person segmentation and part segmentation tasks. titer cpt

train.json and trainval.json · Issue #20 · Jeff-sjtu/CrowdPose

WebJan 20, 2024 · CrowdPose dataset aims to promote performance in crowded cases and make models generalize to different scenarios. View this Dataset -> CVPR View author website Task Human Pose Estimation Annotation Types Keypoint Skeleton 80000 Items … WebEquipped with multi-resolution supervision for training and multi-resolution aggregation for inference, the proposed approach is able to solve the scale variation challenge in bottom-up multi-person pose estimation and localize keypoints more precisely, especially for … WebDec 2, 2024 · In this paper, we propose a novel and efficient method to tackle the problem of pose estimation in the crowd and a new dataset to better evaluate algorithms. Our model consists of two key components: joint-candidate single person pose estimation (SPPE) … titer covid test