15 citations · 42 across the 6 of their papers we have counts for
6 papers
Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds
Chenhang He, Ruihuang Li, Shuai Li +1
Transformer has demonstrated promising performance in many 2D vision tasks. However, it is cumbersome to compute the self-attention on large-scale point cloud data because point cl…
Towards Robust 2D Convolution for Reliable Visual Recognition
Lida Li, Shuai Li, Kun Wang +2
2D convolution (Conv2d), which is responsible for extracting features from the input image, is one of the key modules of a convolutional neural network (CNN). However, Conv2d is vu…
Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation
Ruihuang Li, Shuai Li, Chenhang He +3
Domain adaptive semantic segmentation aims to learn a model with the supervision of source domain data, and produce satisfactory dense predictions on unlabeled target domain. One p…
A Dual Weighting Label Assignment Scheme for Object Detection
Shuai Li, Chenhang He, Ruihuang Li +1
Label assignment (LA), which aims to assign each training sample a positive (pos) and a negative (neg) loss weight, plays an important role in object detection. Existing LA methods…
Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners
Yabin Zhang, Haojian Zhang, Bin Deng +3
Unsupervised domain adaptation (UDA) and semi-supervised learning (SSL) are two typical strategies to reduce expensive manual annotations in machine learning. In order to learn eff…
Spatial Feature Calibration and Temporal Fusion for Effective One-stage Video Instance Segmentation
Minghan Li, Shuai Li, Lida Li +1
Modern one-stage video instance segmentation networks suffer from two limitations. First, convolutional features are neither aligned with anchor boxes nor with ground-truth boundin…