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Found 8 papers, 3 papers with code
Kinematic-aware Hierarchical Attention Network for Human Pose Estimation in Videos
Previous video-based human pose estimation methods have shown promising results by leveraging aggregated features of consecutive frames.
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Pose Estimation
on J-HMDB
OTPose: Occlusion-Aware Transformer for Pose Estimation in Sparsely-Labeled Videos
We achieve state-of-the-art pose estimation results for PoseTrack2017 and PoseTrack2018 datasets and demonstrate the robustness of our approach to occlusion and motion blur in sparsely annotated video data.
HTNet: Anchor-free Temporal Action Localization with Hierarchical Transformers
Temporal action localization (TAL) is a task of identifying a set of actions in a video, which involves localizing the start and end frames and classifying each action instance.
Complete Face Recovery GAN: Unsupervised Joint Face Rotation and De-Occlusion From a Single-View Image
In addition, the lack of high-quality paired data remains an obstacle for both methods.
Joint Dermatological Lesion Classification and Confidence Modeling with Uncertainty Estimation
Deep learning has played a major role in the interpretation of dermoscopic images for detecting skin defects and abnormalities.
ACNet: Mask-Aware Attention with Dynamic Context Enhancement for Robust Acne Detection
To address these problems, we propose an acne detection network which consists of three components, specifically: Composite Feature Refinement, Dynamic Context Enhancement, and Mask-Aware Multi-Attention.
Uncertainty-Aware Human Mesh Recovery From Video by Learning Part-Based 3D Dynamics
Despite the recent success of 3D human reconstruction methods, recovering the accurate and smooth 3D human motion from video is still challenging.
Uncertainty-Aware Mesh Decoder for High Fidelity 3D Face Reconstruction
3D Morphable Model (3DMM) is a statistical model of facial shape and texture using a set of linear basis functions.
