47 citations · 71 across the 6 of their papers we have counts for
6 papers
Few-shot Class-incremental Learning for Classification and Object Detection: A Survey
Jinghua Zhang, Li Liu, Olli Silvén +2
Few-shot Class-Incremental Learning (FSCIL) presents a unique challenge in Machine Learning (ML), as it necessitates the Incremental Learning (IL) of new classes from sparsely labe…
GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer
Zheng Qin, Hao Yu, Changjian Wang +5
We study the problem of extracting accurate correspondences for point cloud registration. Recent keypoint-free methods have shown great potential through bypassing the detection of…
RayMVSNet++: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo
Yifei Shi, Junhua Xi, Dewen Hu +2
Learning-based multi-view stereo (MVS) has by far centered around 3D convolution on cost volumes. Due to the high computation and memory consumption of 3D CNN, the resolution of ou…
SplatFlow: Learning Multi-frame Optical Flow via Splatting
Bo Wang, Yifan Zhang, Jian Li +4
The occlusion problem remains a crucial challenge in optical flow estimation (OFE). Despite the recent significant progress brought about by deep learning, most existing deep learn…
A Forward and Backward Compatible Framework for Few-shot Class-incremental Pill Recognition
Jinghua Zhang, Li Liu, Kai Gao +1
Automatic Pill Recognition (APR) systems are crucial for enhancing hospital efficiency, assisting visually impaired individuals, and preventing cross-infection. However, most exist…
Attentional Feature Refinement and Alignment Network for Aircraft Detection in SAR Imagery
Yan Zhao, Lingjun Zhao, Zhong Liu +3
Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challenging task in SAR Automatic Target Recognition (SAR ATR) areas due to aircraft's extremely discrete appearan…