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cs.CV2025
Diversity-Guided MLP Reduction for Efficient Large Vision Transformers
Chengchao Shen, Hourun Zhu, Gongfan Fang +2
Transformer models achieve excellent scaling property, where the performance is improved with the increment of model capacity. However, large-scale model parameters lead to an unaf…
cs.CV2025
Multiple Object Stitching for Unsupervised Representation Learning
Chengchao Shen, Dawei Liu, Jianxin Wang
Contrastive learning for single object centric images has achieved remarkable progress on unsupervised representation, but suffering inferior performance on the widespread images w…
cs.CV2024
Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning
Chengchao Shen, Jianzhong Chen, Jianxin Wang
The existing contrastive learning methods mainly focus on single-grained representation learning, e.g., part-level, object-level or scene-level ones, thus inevitably neglecting the…