39 lines
2.0 KiB
Markdown
39 lines
2.0 KiB
Markdown
# 2022.11 CS231n学习汇报
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介绍CS231n部分的学习，包含计算机视觉简介、图像分类（K最邻近算法、线性分类）、神经网络以及卷积神经网络部分
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# 2022.12 行人重识别任务汇报
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关于行人重识别第一个阶段的学习汇报
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# 2023.9 行人检测汇报
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关于行人检测系列论文汇报汇总
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* Co-Scale Conv-Attentional Image Transformers
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* LEAPS: End-to-End One-Step Person Search With Learnable Proposals
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* Cascade Transformers for End-to-End Person Search
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* PSTR: End-to-End One-Step Person Search With Transformers
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* FCOS: Fully Convolutional One-Stage Object Detection
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* Optimal Proposal Learning for Deployable End-to-End Pedestrian Detection
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# 2024.1 相关论文阅读汇报
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包含其他方面结合MAE部分的汇报
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* Generic-to-Specific Distillation of Masked Autoencoders
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# 2024.3 2024春季论文汇报
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包含MAE有关工作及文章部分汇总
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* Masked Autoencoders Are Scalable Vision Learners
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* BEiT: BERT Pre-Training of Image Transformers
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* BEIT V2: Masked Image Modeling with Vector-Quantized Visual Tokenizers
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* Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality
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* HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling
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* MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers
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* MultiMAE: Multi-modal Multi-task Masked Autoencoders
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* ConvMAE: Masked Convolution Meets Masked Autoencoders
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* RetroMAE: Pre-training Retrieval-oriented Transformers via Masked Auto-Encoder
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* Siamese Masked Autoencoders
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* Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation
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* Integral Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection
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* Masked Image Modeling with Local Multi-Scale Reconstruction
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* VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
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* VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking
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