CV计算机视觉每日开源代码Paper with code速览-2023.10.26-优快云博客

本文链接：https://blog.youkuaiyun.com/zhangkai950121/article/details/134095870

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1.【基础网络架构：Transformer】（NeurIPS2023）MCUFormer: Deploying Vision Tranformers on Microcontrollers with Limited Memory

论文地址：https://arxiv.org//pdf/2310.16898
开源代码（即将开源）：https://github.com/liangyn22/MCUFormer

2.【Open-Vocabulary Object Detection】LP-OVOD: Open-Vocabulary Object Detection by Linear Probing

论文地址：https://arxiv.org//pdf/2310.17109
开源代码（即将开源）：https://github.com/VinAIResearch/LP-OVOD

3.【视频异常检测】A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection

论文地址：https://arxiv.org//pdf/2310.17650
开源代码（即将开源）：https://github.com/AnasEmad11/C2FPL

4.【视频超分辨率重建】（WACV2024）Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution

论文地址：https://arxiv.org//pdf/2310.17294
开源代码：https://github.com/megvii-research/WACV2024-SAFA

5.【图像增强】（NeurIPS2023）Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

论文地址：https://arxiv.org//pdf/2310.17577
开源代码（即将开源）：GitHub - jinnh/GSAD: Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

6.【领域泛化】SPA: A Graph Spectral Alignment Perspective for Domain Adaptation

论文地址：https://arxiv.org//pdf/2310.17594
开源代码（即将开源）：GitHub - CrownX/SPA

7.【多模态】（EMNLP2023）Evaluating Bias and Fairness in Gender-Neutral Pretrained Vision-and-Language Models

论文地址：https://arxiv.org//pdf/2310.17530
开源代码：GitHub - coastalcph/gender-neutral-vl: [EMNLP 2023] Evaluating Bias and Fairness in Gender-Neutral Pretrained Vision-and-Language Models

8.【多模态】（NeurIPS2023）Cross-modal Active Complementary Learning with Self-refining Correspondence

论文地址：https://arxiv.org//pdf/2310.17468
开源代码（即将开源）：GitHub - QinYang79/CRCL: Cross-modal Active Complementary Learning with Self-refining Correspondence (NeurIPS 2023, Pytorch Code)

9.【自动驾驶】Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models

论文地址：https://arxiv.org//pdf/2310.17642
工程主页：Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models
开源代码（即将开源）：https://github.com/zswang666/drive-anywhere

10.【自动驾驶：BEV】BEVContrast: Self-Supervision in BEV Space for Automotive Lidar Point Clouds

论文地址：https://arxiv.org//pdf/2310.17281
开源代码：https://github.com/valeoai/BEVContrast

11.【自动驾驶：协同感知】（WACV2024）MACP: Efficient Model Adaptation for Cooperative Perception

论文地址：https://arxiv.org//pdf/2310.16870
开源代码：https://github.com/PurdueDigitalTwin/MACP

12.【NeRF】4D-Editor: Interactive Object-level Editing in Dynamic Neural Radiance Fields via 4D Semantic Segmentation

论文地址：https://arxiv.org//pdf/2310.16858
工程主页：4D-Editor: Interactive Object-level Editing in Dynamic Neural Radiance Fields via 4D Semantic Segmentation
代码即将开源

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