MLSP-L22.6
MULTI-TEACHER DISTILLATION FOR INCREMENTAL OBJECT DETECTION
Le Jiang, Hongqiang Cheng, Xiaozhou Ye, Ye Ouyang, AsiaInfo Technologies (China), China
Session:
MLSP-L22: Deep Learning Training Methods I Lecture
Track:
Machine Learning for Signal Processing
Location:
Room 103
Presentation Time:
Fri, 19 Apr, 14:50 - 15:10 (UTC +9)
Session Co-Chairs:
Kai Yu, Shanghai Jiao Tong University and Qiuqiang Kong, Chinese University of Hong Kong
Session MLSP-L22
MLSP-L22.1: LACVIT: A LABEL-AWARE CONTRASTIVE FINE-TUNING FRAMEWORK FOR VISION TRANSFORMERS
Zijun Long, Richard McCreadie, Gerardo Aragon Camarasa, Zaiqiao Meng, The University of Glasgow, United Kingdom of Great Britain and Northern Ireland
MLSP-L22.2: STREAMING ANCHOR LOSS: AUGMENTING SUPERVISION WITH TEMPORAL SIGNIFICANCE
Utkarsh (Oggy) Sarawgi, John Berkowitz, Vineet Garg, Arnav Kundu, Minsik Cho, Sai Srujana Buddi, Saurabh Adya, Ahmed Tewfik, Apple, United States of America
MLSP-L22.3: Continuous Review and Timely Correction: Enhancing the Resistance to Noisy Labels via Self-Not-True Distillation
Jingyi Wang, Da Huang, National University of Defense Technology, China; Xinghao Wu, Beihang University, China; Yuhua Tang, Long Lan, National University of Defense Technology, China
MLSP-L22.4: SEMANTIC-ENHANCED SUPERVISED CONTRASTIVE LEARNING
Pingyue Zhang, Mengyue Wu, Kai Yu, Shanghai Jiao Tong University, China
MLSP-L22.5: AdaPlus: Integrating Nesterov Momentum and Precise Stepsize Adjustment on AdamW Basis
Lei Guan, National University of Defense Technology, China
MLSP-L22.6: MULTI-TEACHER DISTILLATION FOR INCREMENTAL OBJECT DETECTION
Le Jiang, Hongqiang Cheng, Xiaozhou Ye, Ye Ouyang, AsiaInfo Technologies (China), China
Contacts