85 citations · 417 across the 37 of their papers we have counts for
10 papers · 2 filters
CLIP is Also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic Segmentation
Yuqi Lin, Minghao Chen, Wenxiao Wang +5
Weakly supervised semantic segmentation (WSSS) with image-level labels is a challenging task. Mainstream approaches follow a multi-stage framework and suffer from high training cos…
GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds
Honghui Yang, Tong He, Jiaheng Liu +5
Despite the tremendous progress of Masked Autoencoders (MAE) in developing vision tasks such as image and video, exploring MAE in large-scale 3D point clouds remains challenging du…
PriorLane: A Prior Knowledge Enhanced Lane Detection Approach Based on Transformer
Qibo Qiu, Haiming Gao, Wei Hua +2
Lane detection is one of the fundamental modules in self-driving. In this paper we employ a transformer-only method for lane detection, thus it could benefit from the blooming deve…
Towards In-distribution Compatibility in Out-of-distribution Detection
Boxi Wu, Jie Jiang, Haidong Ren +7
Deep neural network, despite its remarkable capability of discriminating targeted in-distribution samples, shows poor performance on detecting anomalous out-of-distribution data. T…
Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local Graph
Honghui Yang, Zili Liu, Xiaopei Wu +4
Two-stage detectors have gained much popularity in 3D object detection. Most two-stage 3D detectors utilize grid points, voxel grids, or sampled keypoints for RoI feature extractio…
Motion-aware Memory Network for Fast Video Salient Object Detection
Xing Zhao, Haoran Liang, Peipei Li +4
Previous methods based on 3DCNN, convLSTM, or optical flow have achieved great success in video salient object detection (VSOD). However, they still suffer from high computational…