Weakly-supervised Learning

227 papers with code • 0 benchmarks • 0 datasets

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Libraries

Use these libraries to find Weakly-supervised Learning models and implementations

Most implemented papers

Weakly Supervised Deep Detection Networks

hbilen/WSDDN CVPR 2016

Weakly supervised learning of object detection is an important problem in image understanding that still does not have a satisfactory solution.

Constrained-CNN losses for weakly supervised segmentation

LIVIAETS/SizeLoss_WSS 12 May 2018

To the best of our knowledge, the method of [Pathak et al., 2015] is the only prior work that addresses deep CNNs with linear constraints in weakly supervised segmentation.

Learning 3D Shape Completion under Weak Supervision

davidstutz/ijcv2018-improved-shape-completion 18 May 2018

We address the problem of 3D shape completion from sparse and noisy point clouds, a fundamental problem in computer vision and robotics.

See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification

wvinzh/WS_DAN_PyTorch 26 Jan 2019

Specifically, for each training image, we first generate attention maps to represent the object's discriminative parts by weakly supervised learning.

Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set

Microsoft/Deep3DFaceReconstruction 20 Mar 2019

Recently, deep learning based 3D face reconstruction methods have shown promising results in both quality and efficiency. However, training deep neural networks typically requires a large volume of data, whereas face images with ground-truth 3D face shapes are scarce.

Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations

jiwoon-ahn/irn CVPR 2019

For generating the pseudo labels, we first identify confident seed areas of object classes from attention maps of an image classification model, and propagate them to discover the entire instance areas with accurate boundaries.

Open-set Label Noise Can Improve Robustness Against Inherent Label Noise

hongxin001/ODNL NeurIPS 2021

Learning with noisy labels is a practically challenging problem in weakly supervised learning.

PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition

shannanyinxiang/pagenet 29 Jul 2022

Utilizing the proposed weakly supervised learning framework, PageNet requires only transcripts to be annotated for real data; however, it can still output detection and recognition results at both the character and line levels, avoiding the labor and cost of labeling bounding boxes of characters and text lines.

How does Disagreement Help Generalization against Label Corruption?

xingruiyu/coteaching_plus 14 Jan 2019

Learning with noisy labels is one of the hottest problems in weakly-supervised learning.