5 papers
SARE: Sample-wise Adaptive Reasoning for Training-free Fine-grained Visual Recognition
Jingxiao Yang, DaLin He, Miao Pan +7
Recent advances in Large Vision-Language Models (LVLMs) have enabled training-free Fine-Grained Visual Recognition (FGVR). However, effectively exploiting LVLMs for FGVR remains ch…
SCHK-HTC: Sibling Contrastive Learning with Hierarchical Knowledge-Aware Prompt Tuning for Hierarchical Text Classification
Ke Xiong, Qian Wu, Wangjie Gan +2
Few-shot Hierarchical Text Classification (few-shot HTC) is a challenging task that involves mapping texts to a predefined tree-structured label hierarchy under data-scarce conditi…
EPIR: An Efficient Patch Tokenization, Integration and Representation Framework for Micro-expression Recognition
Junbo Wang, Liangyu Fu, Yuke Li +3
Micro-expression recognition can obtain the real emotion of the individual at the current moment. Although deep learning-based methods, especially Transformer-based methods, have a…
DiffVC: A Non-autoregressive Framework Based on Diffusion Model for Video Captioning
Junbo Wang, Liangyu Fu, Yuke Li +4
Current video captioning methods usually use an encoder-decoder structure to generate text autoregressively. However, autoregressive methods have inherent limitations such as slow…
SELECT: Detecting Label Errors in Real-world Scene Text Data
Wenjun Liu, Qian Wu, Yifeng Hu +1
We introduce SELECT (Scene tExt Label Errors deteCTion), a novel approach that leverages multi-modal training to detect label errors in real-world scene text datasets. Utilizing an…