all AI news
AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition
May 7, 2024, 4:47 a.m. | Meiqi Cao, Rui Yan, Xiangbo Shu, Guangzhao Dai, Yazhou Yao, Guo-Sen Xie
cs.CV updates on arXiv.org arxiv.org
Abstract: Panoramic Activity Recognition (PAR) aims to identify multi-granularity behaviors performed by multiple persons in panoramic scenes, including individual activities, group activities, and global activities. Previous methods 1) heavily rely on manually annotated detection boxes in training and inference, hindering further practical deployment; or 2) directly employ normal detectors to detect multiple persons with varying size and spatial occlusion in panoramic scenes, blocking the performance gain of PAR. To this end, we consider learning a detector …
abstract adapt arxiv cs.cv deployment detection global identify inference multiple practical recognition training type
More from arxiv.org / cs.CV updates on arXiv.org
Multi-View Spectrogram Transformer for Respiratory Sound Classification
2 days, 22 hours ago |
arxiv.org
GaussianHead: High-fidelity Head Avatars with Learnable Gaussian Derivation
2 days, 22 hours ago |
arxiv.org
OTMatch: Improving Semi-Supervised Learning with Optimal Transport
2 days, 22 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)
@ HelloBetter | Remote
Doctoral Researcher (m/f/div) in Automated Processing of Bioimages
@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena
Seeking Developers and Engineers for AI T-Shirt Generator Project
@ Chevon Hicks | Remote
Senior Applied Data Scientist
@ dunnhumby | London
Principal Data Architect - Azure & Big Data
@ MGM Resorts International | Home Office - US, NV