activity
20172022
most citedCross-Modality Deep Feature Learning for Brain Tumor Segmentation

290 citations · 647 across the 20 of their papers we have counts for

collaborators

24 papers

cs.CV20222 cited

Confidence-guided Centroids for Unsupervised Person Re-Identification

Yunqi Miao, Jiankang Deng, Guiguang Ding +1

Unsupervised person re-identification (ReID) aims to train a feature extractor for identity retrieval without exploiting identity labels. Due to the blind trust in imperfect cluste…

cs.CV20225 cited

Physically-Based Face Rendering for NIR-VIS Face Recognition

Yunqi Miao, Alexandros Lattas, Jiankang Deng +2

Near infrared (NIR) to Visible (VIS) face matching is challenging due to the significant domain gaps as well as a lack of sufficient data for cross-modality model training. To over…

cs.CV20225 cited

Ground Plane Matters: Picking Up Ground Plane Prior in Monocular 3D Object Detection

Fan Yang, Xinhao Xu, Hui Chen +4

The ground plane prior is a very informative geometry clue in monocular 3D object detection (M3OD). However, it has been neglected by most mainstream methods. In this paper, we ide…

cs.CV202281 cited

Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs

Xiaohan Ding, Xiangyu Zhang, Yizhuang Zhou +3

We revisit large kernel design in modern convolutional neural networks (CNNs). Inspired by recent advances in vision transformers (ViTs), in this paper, we demonstrate that using a…

cs.CV2022

Hybrid Routing Transformer for Zero-Shot Learning

De Cheng, Gerong Wang, Bo Wang +3

Zero-shot learning (ZSL) aims to learn models that can recognize unseen image semantics based on the training of data with seen semantics. Recent studies either leverage the global…

cs.CV20224 cited

On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identification

Yunqi Miao, Nianchang Huang, Xiao Ma +2

Visible-infrared person re-identification (VI-ReID) has been challenging due to the existence of large discrepancies between visible and infrared modalities. Most pioneering approa…