The 8th AI City Challenge
원문 초록
The eighth AI City Challenge highlighted the convergence of computer vision and artificial intelligence in areas like retail, warehouse settings, and Intelligent Traffic Systems (ITS), presenting significant research opportunities. The 2024 edition featured five tracks, attracting unprecedented interest from 726 teams in 47 countries and regions. Track 1 dealt with multi-target multi-camera (MTMC) people tracking, highlighting significant enhancements in camera count, character number, 3D annotation, and camera matrices, alongside new rules for 3D tracking and online tracking algorithm encouragement. Track 2 introduced dense video captioning for traffic safety, focusing on pedestrian accidents using multi-camera feeds to improve insights for insurance and prevention. Track 3 required teams to classify driver actions in a naturalistic driving analysis. Track 4 explored fish-eye camera analytics using the FishEye8K dataset. Track 5 focused on motorcycle helmet rule violation detection. The challenge utilized two leaderboards to showcase methods, with participants setting new benchmarks, some surpassing existing state-of-the-art achievements.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
VidChain: Chain-of-Tasks with Metric-based Direct Preference Optimization for Dense Video Captioning
Implicit Location-Caption Alignment via Complementary Masking for Weakly-Supervised Dense Video Captioning
VideoLLM Knows When to Speak: Enhancing Time-Sensitive Video Comprehension with Video-Text Duet Interaction Format
Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
SoccerNet 2024 Challenges Results
COM Kitchens: An Unedited Overhead-view Video Dataset as a Vision-Language Benchmark
토론
이 논문과 연결된 포럼 글이 아직 없습니다.