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Towards Single-Source Domain Generalized Object Detection via Causal Visual Prompts
Chen Li, Huiying Xu, Changxin Gao +3
Single-source Domain Generalized Object Detection (SDGOD), as a cutting-edge research topic in computer vision, aims to enhance model generalization capability in unseen target dom…
Partial Forward Blocking: A Novel Data Pruning Paradigm for Lossless Training Acceleration
Dongyue Wu, Zilin Guo, Jialong Zuo +2
The ever-growing size of training datasets enhances the generalization capability of modern machine learning models but also incurs exorbitant computational costs. Existing data pr…
Structural Pruning via Spatial-aware Information Redundancy for Semantic Segmentation
Dongyue Wu, Zilin Guo, Li Yu +2
In recent years, semantic segmentation has flourished in various applications. However, the high computational cost remains a significant challenge that hinders its further adoptio…
Adaptive Prototype Replay for Class Incremental Semantic Segmentation
Guilin Zhu, Dongyue Wu, Changxin Gao +3
Class incremental semantic segmentation (CISS) aims to segment new classes during continual steps while preventing the forgetting of old knowledge. Existing methods alleviate catas…
Open-Vocabulary Semantic Segmentation with Image Embedding Balancing
Xiangheng Shan, Dongyue Wu, Guilin Zhu +3
Open-vocabulary semantic segmentation is a challenging task, which requires the model to output semantic masks of an image beyond a close-set vocabulary. Although many efforts have…