Dense Semantic Contrast for Self-Supervised Visual Representation Learning
Dense Semantic Contrast for Self-Supervised Visual Representation Learning
Self-supervised representation learning for visual pre-training has achieved remarkable success with sample (instance or pixel) discrimination and semantics discovery of instance, whereas there still exists a non-negligible gap between pre-trained model and downstream dense prediction tasks. Concretely, these downstream tasks require more accurate representation, in other words, the pixels from …