Fine-grained Action Recognition
14 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Fine-grained Action Recognition
MTL-AQA
Latest papers
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN
ParitoshParmar/HalluciNet--PyTorch
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The hallucination task is treated as an auxiliary task, which can be used with any other action related task in a multitask learning setting.
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment
ParitoshParmar/MTL-AQA
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CVPR 2019
Can performance on the task of action quality assessment (AQA) be improved by exploiting a description of the action and its quality?
Unsupervised Feature Learning of Human Actions as Trajectories in Pose Embedding Manifold
In this work we propose a novel temporal pose-sequence modeling framework, which can embed the dynamics of 3D human-skeleton joints to a continuous latent space in an efficient manner.
Analysis of Hand Segmentation in the Wild
In the quest for robust hand segmentation methods, we evaluated the performance of the state of the art semantic segmentation methods, off the shelf and fine-tuned, on existing datasets.
