10 papers · 1 filter
MedFG-VQA: Low-Frequency Memory and Graph Attention for Lightweight Medical VQA
Haowen Gu, Gensheng Pei, Zeren Sun +4
Medical Visual Question Answering (Med-VQA) holds significant promise for clinical decision support, yet faces challenges due to limited annotated data and the high computational d…
Learning 3D Representations for Spatial Intelligence from Unposed Multi-View Images
Bo Zhou, Qiuxia Lai, Zeren Sun +3
Robust 3D representation learning forms the perceptual foundation of spatial intelligence, enabling downstream tasks in scene understanding and embodied AI. However, learning such…
Bilingual Text-to-Motion Generation: A New Benchmark and Baselines
Wanjiang Weng, Xiaofeng Tan, Xiangbo Shu +3
Text-to-motion generation holds significant potential for cross-linguistic applications, yet it is hindered by the lack of bilingual datasets and the poor cross-lingual semantic un…
Beyond Quadratic: Linear-Time Change Detection with RWKV
Zhenyu Yang, Gensheng Pei, Tao Chen +4
Existing paradigms for remote sensing change detection are caught in a trade-off: CNNs excel at efficiency but lack global context, while Transformers capture long-range dependenci…
PCA-Seg: Revisiting Cost Aggregation for Open-Vocabulary Semantic and Part Segmentation
Jianjian Yin, Tao Chen, Yi Chen +4
Recent advances in vision-language models (VLMs) have garnered substantial attention in open-vocabulary semantic and part segmentation (OSPS). However, existing methods extract ima…
Spatio-temporal Decoupled Knowledge Compensator for Few-Shot Action Recognition
Hongyu Qu, Xiangbo Shu, Rui Yan +3
Few-Shot Action Recognition (FSAR) is a challenging task that requires recognizing novel action categories with a few labeled videos. Recent works typically apply semantically coar…
Seeing What Matters: Empowering CLIP with Patch Generation-to-Selection
Gensheng Pei, Tao Chen, Yujia Wang +4
The CLIP model has demonstrated significant advancements in aligning visual and language modalities through large-scale pre-training on image-text pairs, enabling strong zero-shot…
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection
Fenfang Tao, Guo-Sen Xie, Fang Zhao +1
Few-shot anomaly detection (FSAD) aims to detect unseen anomaly regions with the guidance of very few normal support images from the same class. Existing FSAD methods usually find…
AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition
Meiqi Cao, Rui Yan, Xiangbo Shu +3
Panoramic Activity Recognition (PAR) aims to identify multi-granularity behaviors performed by multiple persons in panoramic scenes, including individual activities, group activiti…
GPT4Ego: Unleashing the Potential of Pre-trained Models for Zero-Shot Egocentric Action Recognition
Guangzhao Dai, Xiangbo Shu, Wenhao Wu +2
Vision-Language Models (VLMs), pre-trained on large-scale datasets, have shown impressive performance in various visual recognition tasks. This advancement paves the way for notabl…