TFPose: Direct Human Pose Estimation with Transformers
We propose a human pose estimation framework that solves the task in the regression-based fashion. Unlike previous regression-based methods, which often fall behind those state-of-the-art methods, we formulate the pose estimation task into a sequence prediction problem that can effectively be solved by transformers. Our framework is simple and direct, bypassing the drawbacks of the heatmap-based pose estimation. Moreover, with the attention mechanism in transformers, our proposed framework is able to adaptively attend to the features most relevant to the target keypoints, which largely overcomes the feature misalignment issue of previous regression-based methods and considerably improves the performance. Importantly, our framework can inherently take advantages of the structured relationship between keypoints. Experiments on the MS-COCO and MPII datasets demonstrate that our method can significantly improve the state-of-the-art of regression-based pose estimation and perform comparably with the best heatmap-based pose estimation methods.
Code (0)
등록된 구현이 없습니다.
Tasks
Pose EstimationregressionSimilar Papers 제목 키워드 기반
End-to-End Trainable Multi-Instance Pose Estimation with Transformers
We propose a new end-to-end trainable approach for multi-instance pose estimation by combining a convolutional neural network with a transformer. We cast multi-instance pose estimation from images as a direct set predict…
DecoderKeypoint Detectionobject-detectionObject Detection+1Poseur: Direct Human Pose Regression with Transformers
We propose a direct, regression-based approach to 2D human pose estimation from single images. We formulate the problem as a sequence prediction task, which we solve using a Transformer network. This network directly lea…
2D Human Pose EstimationKeypoint DetectionPose EstimationregressionPoseMamba: Monocular 3D Human Pose Estimation with Bidirectional Global-Local Spatio-Temporal State Space Model
Transformers have significantly advanced the field of 3D human pose estimation (HPE). However, existing transformer-based methods primarily use self-attention mechanisms for spatio-temporal modeling, leading to a quadrat…
3D Human Pose EstimationLong-range modelingMambaMonocular 3D Human Pose Estimation+1CrossFormer: Cross Spatio-Temporal Transformer for 3D Human Pose Estimation
3D human pose estimation can be handled by encoding the geometric dependencies between the body parts and enforcing the kinematic constraints. Recently, Transformer has been adopted to encode the long-range dependencies …
3D Human Pose EstimationPose Estimation3D Human Pose Estimation with Spatial and Temporal Transformers
Transformer architectures have become the model of choice in natural language processing and are now being introduced into computer vision tasks such as image classification, object detection, and semantic segmentation. …
3D Human Pose Estimationimage-classificationImage ClassificationMonocular 3D Human Pose Estimation+4