3 accepted papers
Recent Training-Free Open-Vocabulary Semantic Segmentation (TF-OVSS) leverages a pre-training vision-language model to segment images from open-set visual concepts without training and fine-tuning. The key of TF-OVSS is to improve the local spatial representation of CLIP by leveraging self-correlati…
Synthetic aperture radar (SAR) object detection requires accurate identification and localization of targets at various scales within SAR images. However, background clutter and speckle noise can obscure key features and mislead the knowledge distillation process. To address these challenges, we int…
Existing Weakly Supervised Semantic Segmentation (WSSS) relies on the CNN-based Class Activation Map (CAM) and Transformer-based self-attention map to generate class-specific masks for semantic segmentation. However, CAM and self-attention maps usually cause incomplete segmentation due to classifica…