9 papers with code • 2 benchmarks • 4 datasets

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Most implemented papers

PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization

google-research/pegasus ICML 2020

Recent work pre-training Transformers with self-supervised objectives on large text corpora has shown great success when fine-tuned on downstream NLP tasks including text summarization.

ResT: An Efficient Transformer for Visual Recognition

wofmanaf/ResT NeurIPS 2021

This paper presents an efficient multi-scale vision Transformer, called ResT, that capably served as a general-purpose backbone for image recognition.

A General Approach for Using Deep Neural Network for Digital Watermarking

mingyr/watermarking 8 Mar 2020

Technologies of the Internet of Things (IoT) facilitate digital contents such as images being acquired in a massive way.

DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation

HaoyueBaiZJU/DecAug 17 Dec 2020

To address that, we propose DecAug, a novel decomposed feature representation and semantic augmentation approach for OoD generalization.

Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools

jwwthu/DL4Traffic 18 Mar 2021

Big data has been used widely in many areas including the transportation industry.

MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition

VoiceBeer/MS-MDA 16 Jul 2021

Although several studies have adopted domain adaptation (DA) approaches to tackle this problem, most of them treat multiple EEG data from different subjects and sessions together as a single source domain for transfer, which either fails to satisfy the assumption of domain adaptation that the source has a certain marginal distribution, or increases the difficulty of adaptation.

Long-Tailed Recognition via Weight Balancing

shadealsha/ltr-weight-balancing CVPR 2022

In contrast, weight decay penalizes larger weights more heavily and so learns small balanced weights; the MaxNorm constraint encourages growing small weights within a norm ball but caps all the weights by the radius.

Zero-Shot Logit Adjustment

cdb342/ijcai-2022-zla 25 Apr 2022

As a consequence of our derivation, the aforementioned two properties are incorporated into the classifier training as seen-unseen priors via logit adjustment.

MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training

nvlabs/minvis 3 Aug 2022

By only training a query-based image instance segmentation model, MinVIS outperforms the previous best result on the challenging Occluded VIS dataset by over 10% AP.