collaborators

5 papers

cs.CV20241 cited

Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic Segmentation

Bingfeng Zhang, Siyue Yu, Yunchao Wei +2

Weakly supervised semantic segmentation has witnessed great achievements with image-level labels. Several recent approaches use the CLIP model to generate pseudo labels for trainin…

cs.CV2024

Continual Segmentation with Disentangled Objectness Learning and Class Recognition

Yizheng Gong, Siyue Yu, Xiaoyang Wang +1

Most continual segmentation methods tackle the problem as a per-pixel classification task. However, such a paradigm is very challenging, and we find query-based segmenters with bui…

cs.CV20241 cited

Towards the Uncharted: Density-Descending Feature Perturbation for Semi-supervised Semantic Segmentation

Xiaoyang Wang, Huihui Bai, Limin Yu +2

Semi-supervised semantic segmentation allows model to mine effective supervision from unlabeled data to complement label-guided training. Recent research has primarily focused on c…

cs.CV2024

SFC: Shared Feature Calibration in Weakly Supervised Semantic Segmentation

Xinqiao Zhao, Feilong Tang, Xiaoyang Wang +1

Image-level weakly supervised semantic segmentation has received increasing attention due to its low annotation cost. Existing methods mainly rely on Class Activation Mapping (CAM)…

cs.CV2023

Synchronize Feature Extracting and Matching: A Single Branch Framework for 3D Object Tracking

Teli Ma, Mengmeng Wang, Jimin Xiao +2

Siamese network has been a de facto benchmark framework for 3D LiDAR object tracking with a shared-parametric encoder extracting features from template and search region, respectiv…