153 citations · 217 across the 11 of their papers we have counts for
11 papers
TALENT: Target-aware Efficient Tuning for Referring Image Segmentation
Shuo Jin, Siyue Yu, Bingfeng Zhang +3
Referring image segmentation aims to segment specific targets based on a natural text expression. Recently, parameter-efficient tuning (PET) has emerged as a promising paradigm. Ho…
TF-SSD: A Strong Pipeline via Synergic Mask Filter for Training-free Co-salient Object Detection
Zhijin He, Shuo Jin, Siyue Yu +4
Co-salient Object Detection (CoSOD) aims to segment salient objects that consistently appear across a group of related images. Despite the notable progress achieved by recent train…
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…
Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detection
Siyue Yu, Jimin Xiao, Bingfeng Zhang +1
Co-salient object detection, with the target of detecting co-existed salient objects among a group of images, is gaining popularity. Recent works use the attention mechanism or ext…
Dynamic Feature Regularized Loss for Weakly Supervised Semantic Segmentation
Bingfeng Zhang, Jimin Xiao, Yao Zhao
We focus on tackling weakly supervised semantic segmentation with scribble-level annotation. The regularized loss has been proven to be an effective solution for this task. However…
Fast Pixel-Matching for Video Object Segmentation
Siyue Yu, Jimin Xiao, BingFeng Zhang +1
Video object segmentation, aiming to segment the foreground objects given the annotation of the first frame, has been attracting increasing attentions. Many state-of-the-art approa…
Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
Bingfeng Zhang, Jimin Xiao, Jianbo Jiao +2
Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmenta…
Self-Guided and Cross-Guided Learning for Few-Shot Segmentation
Bingfeng Zhang, Jimin Xiao, Terry Qin
Few-shot segmentation has been attracting a lot of attention due to its effectiveness to segment unseen object classes with a few annotated samples. Most existing approaches use ma…
Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence
Siyue Yu, Bingfeng Zhang, Jimin Xiao +1
Sparse labels have been attracting much attention in recent years. However, the performance gap between weakly supervised and fully supervised salient object detection methods is h…
Fast Template Matching and Update for Video Object Tracking and Segmentation
Mingjie Sun, Jimin Xiao, Eng Gee Lim +2
In this paper, the main task we aim to tackle is the multi-instance semi-supervised video object segmentation across a sequence of frames where only the first-frame box-level groun…
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach
Bingfeng Zhang, Jimin Xiao, Yunchao Wei +2
Weakly supervised semantic segmentation is a challenging task as it only takes image-level information as supervision for training but produces pixel-level predictions for testing.…