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HUWSOD: Holistic Self-training for Unified Weakly Supervised Object Detection
Liujuan Cao, Jianghang Lin, Zebo Hong +4
Most WSOD methods rely on traditional object proposals to generate candidate regions and are confronted with unstable training, which easily gets stuck in a poor local optimum. In…
LIPT: Latency-aware Image Processing Transformer
Junbo Qiao, Wei Li, Haizhen Xie +5
Transformer is leading a trend in the field of image processing. Despite the great success that existing lightweight image processing transformers have achieved, they are tailored…
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li +5
Knowledge distillation (KD) is a promising yet challenging model compression technique that transfers rich learning representations from a well-performing but cumbersome teacher mo…
Class-Imbalanced Semi-Supervised Learning for Large-Scale Point Cloud Semantic Segmentation via Decoupling Optimization
Mengtian Li, Shaohui Lin, Zihan Wang +3
Semi-supervised learning (SSL), thanks to the significant reduction of data annotation costs, has been an active research topic for large-scale 3D scene understanding. However, the…
Rethinking Centered Kernel Alignment in Knowledge Distillation
Zikai Zhou, Yunhang Shen, Shitong Shao +2
Knowledge distillation has emerged as a highly effective method for bridging the representation discrepancy between large-scale models and lightweight models. Prevalent approaches…