98 citations · 359 across the 22 of their papers we have counts for
28 papers · 1 filter
Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection
Ziteng Cui, Guo-Jun Qi, Lin Gu +3
Dark environment becomes a challenge for computer vision algorithms owing to insufficient photons and undesirable noise. To enhance object detection in a dark environment, we propo…
Dual-Flattening Transformers through Decomposed Row and Column Queries for Semantic Segmentation
Ying Wang, Chiuman Ho, Wenju Xu +3
It is critical to obtain high resolution features with long range dependency for dense prediction tasks such as semantic segmentation. To generate high-resolution output of size $H…
Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition
Guangwei Gao, Yi Yu, Jian Yang +2
Cross-resolution face recognition (CRFR), which is important in intelligent surveillance and biometric forensics, refers to the problem of matching a low-resolution (LR) probe face…
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations
Xiang Gao, Wei Hu, Guo-Jun Qi
3D object representation learning is a fundamental challenge in computer vision to infer about the 3D world. Recent advances in deep learning have shown their efficiency in 3D obje…
FLAT: Few-Shot Learning via Autoencoding Transformation Regularizers
Haohang Xu, Hongkai Xiong, Guojun Qi
One of the most significant challenges facing a few-shot learning task is the generalizability of the (meta-)model from the base to the novel categories. Most of existing few-shot…
AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups
Feng Lin, Haohang Xu, Houqiang Li +2
Self-supervised learning by predicting transformations has demonstrated outstanding performances in both unsupervised and (semi-)supervised tasks. Among the state-of-the-art method…