Hand Segmentation
11 papers with code • 0 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Hand Segmentation
EgoHands
EYTH
HandNet
ObMan-Ego
Most implemented papers
HGR-Net: A Fusion Network for Hand Gesture Segmentation and Recognition
Plrbear/HGR-Net
•
•
We propose a two-stage convolutional neural network (CNN) architecture for robust recognition of hand gestures, called HGR-Net, where the first stage performs accurate semantic segmentation to determine hand regions, and the second stage identifies the gesture.
VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail Checkout
guglielmocamporese/hands-segmentation-pytorch
•
•
Multi-class product counting and recognition identifies product items from images or videos for automated retail checkout.
Hand Segmentation for Hand-Object Interaction from Depth map
Thus, we propose hand segmentation method for hand-object interaction using only a depth map.
Depth Adaptive Deep Neural Network for Semantic Segmentation
To overcome this challenge, we develop a neural network which is able to adapt the receptive field not only for each layer but also for each neuron at the spatial location.
Analysis of Hand Segmentation in the Wild
In the quest for robust hand segmentation methods, we evaluated the performance of the state of the art semantic segmentation methods, off the shelf and fine-tuned, on existing datasets.
Attention is All We Need: Nailing Down Object-centric Attention for Egocentric Activity Recognition
Our model is built on the observation that egocentric activities are highly characterized by the objects and their locations in the video.
Generalizing Hand Segmentation in Egocentric Videos With Uncertainty-Guided Model Adaptation
cai-mj/UMA
•
•
CVPR 2020
To this end, we propose a Bayesian CNN-based model adaptation framework for hand segmentation, which introduces and considers two key factors: 1) prediction uncertainty when the model is applied in a new domain and 2) common information about hand shapes shared across domains.
Ego2Hands: A Dataset for Egocentric Two-hand Segmentation and Detection
Hand segmentation and detection in truly unconstrained RGB-based settings is important for many applications.
Foreground-Aware Stylization and Consensus Pseudo-Labeling for Domain Adaptation of First-Person Hand Segmentation
We validated our method on domain adaptation of hand segmentation from real and simulation images.
Generative Adversarial Network for Future Hand Segmentation from Egocentric Video
vjwq/egogan
•
•
We introduce the novel problem of anticipating a time series of future hand masks from egocentric video.
