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1.【基础网络架构】（NeurIPS2023）AiluRus: A Scalable ViT Framework for Dense Prediction
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论文地址：https://arxiv.org//pdf/2311.01197
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开源代码（即将开源）：GitHub - caddyless/AiluRus: The source code for NeurIPS2023 paper "AiluRus: A Scalable ViT Framework for Dense Prediction"
2.【基础网络架构：Transformer】Scattering Vision Transformer: Spectral Mixing Matters
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论文地址：https://arxiv.org//pdf/2311.01310
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工程主页：Scattering Vision Transformer: Spectral Mixing Matters
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开源代码：GitHub - badripatro/svt: Scattering Vision Transformer
3.【异常检测】（WACV2024）Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation
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论文地址：https://arxiv.org//pdf/2311.01117
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开源代码（即将开源）：GitHub - VitjanZ/3DSR: Official implementation of the WACV2024 paper: Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation
4.【超分辨率重建】（WACV2024）VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic Data
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论文地址：https://arxiv.org//pdf/2311.00996
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开源代码（即将开源）：GitHub - Kiteretsu77/VCISR-official
5.【行人重识别】Learning Intra and Inter-Camera Invariance for Isolated Camera Supervised Person Re-identification
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论文地址：https://arxiv.org//pdf/2311.01155
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开源代码（即将开源）：Terminator8758/IICI · GitHub
6.【多模态】VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning
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论文地址：https://arxiv.org//pdf/2311.00990
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工程主页：VideoDreamer
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代码即将开源
7.【数字人】LaughTalk: Expressive 3D Talking Head Generation with Laughter
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论文地址：https://arxiv.org//pdf/2311.00994
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工程主页：LaughTalk: Expressive 3D Talking Head Generation with Laughter
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代码即将开源
8.【Diffusion】（NeurIPS2023）Optimal Transport-Guided Conditional Score-Based Diffusion Models
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论文地址：https://arxiv.org//pdf/2311.01226
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开源代码：GitHub - XJTU-XGU/OTCS: Code for "Optimal Transport-Guided Conditional Score-Based Diffusion Model (NeurIPS, 8,7,7,6)"
9.【Diffusion】（NeurIPS2023）Gaussian Mixture Solvers for Diffusion Models
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论文地址：https://arxiv.org//pdf/2311.00941
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开源代码（即将开源）：GitHub - Guohanzhong/GMS
10.【图像编辑】The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing
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论文地址：https://arxiv.org//pdf/2311.01410
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工程主页：SDE Drag
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开源代码：GitHub - ML-GSAI/SDE-Drag
11.【类别增量学习】Robust Feature Learning and Global Variance-Driven Classifier Alignment for Long-Tail Class Incremental Learning
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论文地址：https://arxiv.org//pdf/2311.01227
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开源代码（即将开源）：GitHub - JAYATEJAK/GVAlign: Robust Feature Learning and Global Variance-Driven Classifier Alignment for Long-Tail Class Incremental Learning
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