Importance Of Self-Consistency In Active Learning For Semantic Segmentation

Importance of Self-Consistency in Active Learning for Semantic Segmentation

Alireza Golestaneh

Embodied Active Domain Adaptation for Semantic Segmentation via Informative Path Planning

ViewAL: Active Learning With Viewpoint Entropy for Semantic Segmentation

ComputerVisionFoundation Videos

Perceptual Consistency in Video Segmentation

ComputerVisionFoundation Videos

[CVPR 2021] Self-supervised Augmentation Consistency for Adapting Semantic Segmentation

Visual Inference

ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation (CVPR 2020)

Matthias Niessner

A Closer Look at Self training for Zero Label Semantic Segmentation

Learning with Limited and Imperfect Data

Talk by R. Sheikh on Gradient and Log-based Active Learning for Semantic Segmentation... (ICRA'20)

Cyrill Stachniss

Semi Supervised Semantic Segmentation with Cross Consistency Training

Self-Supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation

ComputerVisionFoundation Videos

Using self-supervised and active learning for data curation

[CVPR2022 Oral] Towards Fewer Annotations: Active Learning for Domain Adaptive Semantic Segmentation

Active Learning for Improved Semi-Supervised Semantic Segmentation in Satellite Images

ComputerVisionFoundation Videos

Semi-Supervised Semantic Segmentation With Cross-Consistency Training

ComputerVisionFoundation Videos

Evaluation: LLM robustness and self-consistency

Generative AI at MIT

Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks

ComputerVisionFoundation Videos

Introducing Geometry in Active Learning for Image Segmentation

Ksenia Konyushkova

CVPR22 - Active Learning for Open-set Annotation

Senior project : The study of active learning for segmantic segmentation

Kotchaporn Klomjai