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Bryan M. Williams

4 accepted papers

2024

Weakly Supervised Co-training with Swapping Assignments for Semantic Segmentation

ECCV 2024poster

"Class activation maps (CAMs) are commonly employed in weakly supervised semantic segmentation (WSSS) to produce pseudo-labels. Due to incomplete or excessive class activation, existing studies often resort to offline CAM refinement, introducing additional stages or proposing offline modules. This c…

2023

A Probabilistic Attention Model With Occlusion-Aware Texture Regression for 3D Hand Reconstruction From a Single RGB Image

CVPR 2023poster

Recently, deep learning based approaches have shown promising results in 3D hand reconstruction from a single RGB image. These approaches can be roughly divided into model-based approaches, which are heavily dependent on the model's parameter space, and model-free approaches, which require large num…

2022

Graph-Context Attention Networks for Size-Varied Deep Graph Matching

CVPR 2022poster

Deep learning for graph matching has received growing interest and developed rapidly in the past decade. Although recent deep graph matching methods have shown excellent performance on matching between graphs of equal size in the computer vision area, the size-varied graph matching problem, where th…

Cited by 29PDFcodeScholar
2019

Learning Active Contour Models for Medical Image Segmentation

CVPR 2019poster

Image segmentation is an important step in medical image processing and has been widely studied and developed for refinement of clinical analysis and applications. New models based on deep learning have improved results but are restricted to pixel-wise fitting of the segmentation map. Our aim was to…

Cited by 389PDFcodeScholar