2 citations · 2 across the 1 of their papers we have counts for
4 papers
Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformers
Tsung-Wei Ke, Jyh-Jing Hwang, Yunhui Guo +2
Unsupervised semantic segmentation aims to discover groupings within and across images that capture object and view-invariance of a category without external supervision. Grouping…
Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Tsung-Wei Ke, Jyh-Jing Hwang, Stella X. Yu
Weakly supervised segmentation requires assigning a label to every pixel based on training instances with partial annotations such as image-level tags, object bounding boxes, label…
Adversarial Structure Matching for Structured Prediction Tasks
Jyh-Jing Hwang, Tsung-Wei Ke, Jianbo Shi +1
Pixel-wise losses, e.g., cross-entropy or L2, have been widely used in structured prediction tasks as a spatial extension of generic image classification or regression. However, it…
Adaptive Affinity Fields for Semantic Segmentation
Tsung-Wei Ke, Jyh-Jing Hwang, Ziwei Liu +1
Semantic segmentation has made much progress with increasingly powerful pixel-wise classifiers and incorporating structural priors via Conditional Random Fields (CRF) or Generative…