6 papers
Progressive: A Teacher-Student Progressive Co-Evolving Knowledge Distillation Method for Substantial Model Compression
Tiancong Cheng, Ying Zhang, Zhiwen Yu +2
Knowledge distillation (KD) is a widely utilized technique for transferring knowledge from a large model (the teacher) to a smaller model (the student). Owing to its flexibility an…
OpenAVS: Training-Free Open-Vocabulary Audio Visual Segmentation with Foundational Models
Shengkai Chen, Yifang Yin, Jinming Cao +3
Audio-visual segmentation aims to separate sounding objects from videos by predicting pixel-level masks based on audio signals. Existing methods primarily concentrate on closed-set…
TAIL: Text-Audio Incremental Learning
Yingfei Sun, Xu Gu, Wei Ji +3
Many studies combine text and audio to capture multi-modal information but they overlook the model's generalization ability on new datasets. Introducing new datasets may affect the…
ShapeMoiré: Channel-Wise Shape-Guided Network for Image Demoiréing
Jinming Cao, Sicheng Shen, Qiu Zhou +3
Photographing optoelectronic displays often introduces unwanted moiré patterns due to analog signal interference between the pixel grids of the display and the camera sensor array…
Prompt-Based Spatio-Temporal Graph Transfer Learning
Junfeng Hu, Xu Liu, Zhencheng Fan +4
Spatio-temporal graph neural networks have proven efficacy in capturing complex dependencies for urban computing tasks such as forecasting and kriging. Yet, their performance is co…
Manifold-Aware Local Feature Modeling for Semi-Supervised Medical Image Segmentation
Sicheng Shen, Jinming Cao, Yifang Yin +1
Achieving precise medical image segmentation is vital for effective treatment planning and accurate disease diagnosis. Traditional fully-supervised deep learning methods, though hi…