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Found 6 papers, 4 papers with code
Weakly Supervised Co-training with Swapping Assignments for Semantic Segmentation
Class activation maps (CAMs) are commonly employed in weakly supervised semantic segmentation (WSSS) to produce pseudo-labels.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
3D Points Splatting for Real-Time Dynamic Hand Reconstruction
This is followed by a self-adaptive deformation that deforms the hand from the canonical space to the target pose, adapting to the dynamic changing of canonical points which, in contrast to the common practice of subdividing the MANO model, offers greater flexibility and results in improved geometry fitting.
A Probabilistic Attention Model with Occlusion-aware Texture Regression for 3D Hand Reconstruction from a Single RGB Image
The experimental results demonstrate our probabilistic model's state-of-the-art accuracy in 3D hand and texture reconstruction from a single image in both training schemes, including in the presence of severe occlusions.
Ranked #2 on
3D Hand Pose Estimation
on HO-3D
Graph-Context Attention Networks for Size-Varied Deep Graph Matching
Deep learning for graph matching has received growing interest and developed rapidly in the past decade.
Ranked #4 on
Graph Matching
on PASCAL VOC
(matching accuracy metric)
Multi-Branch with Attention Network for Hand-Based Person Recognition
In this paper, we propose a novel hand-based person recognition method for the purpose of criminal investigations since the hand image is often the only available information in cases of serious crime such as sexual abuse.
Hand-Based Person Identification using Global and Part-Aware Deep Feature Representation Learning
Our proposed method, Global and Part-Aware Network (GPA-Net), creates global and local branches on the conv-layer for learning robust discriminative global and part-level features.
