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Found 11 papers, 6 papers with code
Making Your First Choice: To Address Cold Start Problem in Vision Active Learning
However, we uncover a striking contradiction to this promise: active learning fails to select data as efficiently as random selection at the first few choices.
Automatic tagging of knowledge points for K12 math problems
In this paper, K12 math problems taken as the research object, the LABS model based on label-semantic attention and multi-label smoothing combining textual features is proposed to improve the automatic tagging of knowledge points for math problems.
To Answer or Not to Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning
Machine Reading Comprehension with Unanswerable Questions is a difficult NLP task, challenged by the questions which can not be answered from passages.
BEIKE NLP at SemEval-2022 Task 4: Prompt-Based Paragraph Classification for Patronizing and Condescending Language Detection
PCL detection task is aimed at identifying and categorizing language that is patronizing or condescending towards vulnerable communities in the general media. Compared to other NLP tasks of paragraph classification, the negative language presented in the PCL detection task is usually more implicit and subtle to be recognized, making the performance of common text-classification approaches disappointed.
NAFSSR: Stereo Image Super-Resolution Using NAFNet
This paper inherits a strong and simple image restoration model, NAFNet, for single-view feature extraction and extends it by adding cross attention modules to fuse features between views to adapt to binocular scenarios.
Simple Baselines for Image Restoration
Although there have been significant advances in the field of image restoration recently, the system complexity of the state-of-the-art (SOTA) methods is increasing as well, which may hinder the convenient analysis and comparison of methods.
Ranked #1 on
Deblurring
on MSU BASED
Improving Image Restoration by Revisiting Global Information Aggregation
Our TLC converts global operations to local ones only during inference so that they aggregate features within local spatial regions rather than the entire large images.
Ranked #1 on
Image Defocus Deblurring
on DPD
Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
A detailed description of all models developed in the challenge is provided in this paper.
Multi-task Graph Convolutional Neural Network for Calcification Morphology and Distribution Analysis in Mammograms
In this study, we proposed a multi-task deep graph convolutional network (GCN) method for the automatic characterization of morphology and distribution of microcalcifications in mammograms.
HINet: Half Instance Normalization Network for Image Restoration
Specifically, we present a novel block: Half Instance Normalization Block (HIN Block), to boost the performance of image restoration networks.
Ranked #2 on
Single Image Deraining
on Test2800
Points as Queries: Weakly Semi-supervised Object Detection by Points
We propose a novel point annotated setting for the weakly semi-supervised object detection task, in which the dataset comprises small fully annotated images and large weakly annotated images by points.
