Search Results for author:
Found 10 papers, 3 papers with code
TrackID3x3: A Dataset and Algorithm for Multi-Player Tracking with Identification and Pose Estimation in 3x3 Basketball Full-court Videos
In this paper, we propose the TrackID3x3 dataset, the first publicly available comprehensive dataset specifically designed for multi-player tracking, player identification, and pose estimation in 3x3 basketball scenarios.
LLM-AutoDiff: Auto-Differentiate Any LLM Workflow
Large Language Models (LLMs) have reshaped natural language processing, powering applications from multi-hop retrieval and question answering to autonomous agent workflows.
Enhanced Multi-Object Tracking Using Pose-based Virtual Markers in 3x3 Basketball
While pedestrian tracking has advanced with Tracking-by-Detection MOT, team sports like basketball pose unique challenges.
A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations
However, a comprehensive investigation into WM fiber tracts between Eastern and Western populations is challenged due to the lack of a cross-population WM atlas and the large site-specific variability of dMRI data.
HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings
Out-of-distribution (OOD) detection is an important topic for real-world machine learning systems, but settings with limited in-distribution samples have been underexplored.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Synthesis of Temporally-Robust Policies for Signal Temporal Logic Tasks using Reinforcement Learning
The second objective is to maximize the worst-case spatial robustness value within a bounded time shift.
Deep learning radiomics for assessment of gastroesophageal varices in people with compensated advanced chronic liver disease
Validation analysis revealed that the AUCs of DLRP were 0. 91 for GEV (95% CI 0. 90 to 0. 93, p < 0. 05) and 0. 88 for HRV (95% CI 0. 86 to 0. 89, p < 0. 01), which were significantly and robustly better than canonical risk indicators, including the value of LSM and SSM.
Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection
We study the challenging incremental few-shot object detection (iFSD) setting.
Extending One-Stage Detection with Open-World Proposals
In many applications, such as autonomous driving, hand manipulation, or robot navigation, object detection methods must be able to detect objects unseen in the training set.
Zombie Account Detection Based on Community Detection and Uneven Assignation PageRank
In tradition, PageRank algorithm is used to detect zombie accounts.
