77 citations · 206 across the 29 of their papers we have counts for
16 papers · 1 filter
Hierarchical Point-based Active Learning for Semi-supervised Point Cloud Semantic Segmentation
Zongyi Xu, Bo Yuan, Shanshan Zhao +2
Impressive performance on point cloud semantic segmentation has been achieved by fully-supervised methods with large amounts of labelled data. As it is labour-intensive to acquire…
ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolution
Mingjin Zhang, Chi Zhang, Qiming Zhang +3
Single hyperspectral image super-resolution (single-HSI-SR) aims to restore a high-resolution hyperspectral image from a low-resolution observation. However, the prevailing CNN-bas…
Attention Consistency Refined Masked Frequency Forgery Representation for Generalizing Face Forgery Detection
Decheng Liu, Tao Chen, Chunlei Peng +3
Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security. Existing forg…
PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow
Lin Yuan, Kai Liang, Xiao Pu +5
This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single…
MMNet: Multi-Collaboration and Multi-Supervision Network for Sequential Deepfake Detection
Ruiyang Xia, Decheng Liu, Jie Li +3
Advanced manipulation techniques have provided criminals with opportunities to make social panic or gain illicit profits through the generation of deceptive media, such as forged f…
SAR-to-Optical Image Translation via Thermodynamics-inspired Network
Mingjin Zhang, Jiamin Xu, Chengyu He +3
Synthetic aperture radar (SAR) is prevalent in the remote sensing field but is difficult to interpret in human visual perception. Recently, SAR-to-optical (S2O) image conversion me…
Selecting Learnable Training Samples is All DETRs Need in Crowded Pedestrian Detection
Feng Gao, Jiaxu Leng, Gan Ji +1
DEtection TRansformer (DETR) and its variants (DETRs) achieved impressive performance in general object detection. However, in crowded pedestrian detection, the performance of DETR…
Rethinking k-means from manifold learning perspective
Quanxue Gao, Qianqian Wang, Han Lu +2
Although numerous clustering algorithms have been developed, many existing methods still leverage k-means technique to detect clusters of data points. However, the performance of k…
Unsupervised Visible-Infrared Person ReID by Collaborative Learning with Neighbor-Guided Label Refinement
De Cheng, Xiaojian Huang, Nannan Wang +3
Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims at learning modality-invariant features from unlabeled cross-modality dataset, which is crucial f…
Efficient Bilateral Cross-Modality Cluster Matching for Unsupervised Visible-Infrared Person ReID
De Cheng, Lingfeng He, Nannan Wang +3
Unsupervised visible-infrared person re-identification (USL-VI-ReID) aims to match pedestrian images of the same identity from different modalities without annotations. Existing wo…
Adapt and Align to Improve Zero-Shot Sketch-Based Image Retrieval
Shiyin Dong, Mingrui Zhu, Nannan Wang +1
Zero-shot sketch-based image retrieval (ZS-SBIR) is challenging due to the cross-domain nature of sketches and photos, as well as the semantic gap between seen and unseen image dis…
Boosting Weakly-Supervised Temporal Action Localization with Text Information
Guozhang Li, De Cheng, Xinpeng Ding +3
Due to the lack of temporal annotation, current Weakly-supervised Temporal Action Localization (WTAL) methods are generally stuck into over-complete or incomplete localization. In…
Weakly-Supervised Temporal Action Localization with Bidirectional Semantic Consistency Constraint
Guozhang Li, De Cheng, Xinpeng Ding +3
Weakly Supervised Temporal Action Localization (WTAL) aims to classify and localize temporal boundaries of actions for the video, given only video-level category labels in the trai…
SAWU-Net: Spatial Attention Weighted Unmixing Network for Hyperspectral Images
Lin Qi, Xuewen Qin, Feng Gao +2
Hyperspectral unmixing is a critical yet challenging task in hyperspectral image interpretation. Recently, great efforts have been made to solve the hyperspectral unmixing task via…
Hierarchical Supervision and Shuffle Data Augmentation for 3D Semi-Supervised Object Detection
Chuandong Liu, Chenqiang Gao, Fangcen Liu +3
State-of-the-art 3D object detectors are usually trained on large-scale datasets with high-quality 3D annotations. However, such 3D annotations are often expensive and time-consumi…
Few-shot Font Generation by Learning Style Difference and Similarity
Xiao He, Mingrui Zhu, Nannan Wang +2
Few-shot font generation (FFG) aims to preserve the underlying global structure of the original character while generating target fonts by referring to a few samples. It has been a…