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Found 5 papers, 3 papers with code
BEM: Balanced and Entropy-based Mix for Long-Tailed Semi-Supervised Learning
To this end, this paper introduces the Balanced and Entropy-based Mix (BEM), a pioneering mixing approach to re-balance the class distribution of both data quantity and uncertainty.
EfficientRep:An Efficient Repvgg-style ConvNets with Hardware-aware Neural Network Design
Thus, how to design a neural network to efficiently use the computing ability and memory bandwidth of hardware is a critical problem.
YOLOv6 v3.0: A Full-Scale Reloading
For a glimpse of performance, our YOLOv6-N hits 37. 5% AP on the COCO dataset at a throughput of 1187 FPS tested with an NVIDIA Tesla T4 GPU.
Ranked #1 on
Object Detection
on COCO 2017 val
Semi-MAE: Masked Autoencoders for Semi-supervised Vision Transformers
To alleviate this issue, inspired by masked autoencoder (MAE), which is a data-efficient self-supervised learner, we propose Semi-MAE, a pure ViT-based SSL framework consisting of a parallel MAE branch to assist the visual representation learning and make the pseudo labels more accurate.
Representation Learning
Semi-Supervised Image Classification
YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications
The YOLO community has prospered overwhelmingly to enrich its use in a multitude of hardware platforms and abundant scenarios.
Ranked #14 on
Object Detection
on COCO-O
