143 citations · 304 across the 7 of their papers we have counts for
7 papers
Label What Matters: Modality-Balanced and Difficulty-Aware Multimodal Active Learning
Yuqiao Zeng, Xu Wang, Tengfei Liang +3
Multimodal learning integrates complementary information from different modalities such as image, text, and audio to improve model performance, but its success relies on large-scal…
Bridging the Gap: Multi-Level Cross-Modality Joint Alignment for Visible-Infrared Person Re-Identification
Tengfei Liang, Yi Jin, Wu Liu +3
Visible-Infrared person Re-IDentification (VI-ReID) is a challenging cross-modality image retrieval task that aims to match pedestrians' images across visible and infrared cameras.…
Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation
Tianjiao Jiang, Yi Jin, Tengfei Liang +2
Image semantic segmentation aims at the pixel-level classification of images, which has requirements for both accuracy and speed in practical application. Existing semantic segment…
Camera-aware Style Separation and Contrastive Learning for Unsupervised Person Re-identification
Xue Li, Tengfei Liang, Yi Jin +2
Unsupervised person re-identification (ReID) is a challenging task without data annotation to guide discriminative learning. Existing methods attempt to solve this problem by clust…
MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification
Yajun Gao, Tengfei Liang, Yi Jin +4
The RGB-infrared cross-modality person re-identification (ReID) task aims to recognize the images of the same identity between the visible modality and the infrared modality. Exist…
CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification
Tengfei Liang, Yi Jin, Yajun Gao +4
Visible-infrared cross-modality person re-identification is a challenging ReID task, which aims to retrieve and match the same identity's images between the heterogeneous visible a…
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising
Tengfei Liang, Yi Jin, Yidong Li +3
In the past few decades, to reduce the risk of X-ray in computed tomography (CT), low-dose CT image denoising has attracted extensive attention from researchers, which has become a…