Search Results for author:
Found 4 papers, 3 papers with code
Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head
Accurate localization of cephalometric landmarks holds great importance in the fields of orthodontics and orthognathics due to its potential for automating key point labeling.
Chaotic World: A Large and Challenging Benchmark for Human Behavior Understanding in Chaotic Events
Understanding and analyzing human behaviors (actions and interactions of people), voices, and sounds in chaotic events is crucial in many applications, e. g., crowd management, emergency response services.
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior Understanding
More specifically, our dataset contains 50 hours of annotated videos to localize relevant animal behavior segments in long videos for the video grounding task, 30K video sequences for the fine-grained multi-label action recognition task, and 33K frames for the pose estimation task, which correspond to a diverse range of animals with 850 species across 6 major animal classes.
Ranked #2 on
Action Recognition
on Animal Kingdom
A Novel Multi-task Deep Learning Model for Skin Lesion Segmentation and Classification
In this study, a multi-task deep neural network is proposed for skin lesion analysis.
