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A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”
[NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS). It is also a PyTorch implementation of the NeurIPS 2020 paper 'Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect'.
该系列的目的是让读者可以在基础的pytorch上，不依赖任何其他现成的外部库，从零开始理解并实现一个大语言模型的所有组成部分，以及训练微调代码，因此读者仅需python，pytorch和最基础深度学习背景知识即可。
A pytroch reimplementation of "Bilinear Attention Network", "Intra- and Inter-modality Attention", "Learning Conditioned Graph Structures", "Learning to count object", "Bottom-up top-down" for Visual Question Answering 2.0
Using Pytorch to implement a ResNet50 for Cross-Age Face Recognition
[ECCV 2022] A generalized long-tailed challenge that incorporates both the conventional class-wise imbalance and the overlooked attribute-wise imbalance within each class. The proposed IFL together with other baselines are also included.
Code for the Scene Graph Generation part of CVPR 2019 oral paper: "Learning to Compose Dynamic Tree Structures for Visual Contexts"
基于Claude与Obsidian/WebUI的个人知识管理、更新、交互系统“茵蒂克丝.skill”（LLM Wiki）。同济大学工程智能研究院出品~
A Complete PyTorch 1.0 Implementation of Gated Graph Sequence Neural Networks (GGNN)
Using Tensorflow to implement a ResNet50 for Cross-Age Face Recognition
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