CV计算机视觉每日开源代码Paper with code速览-2023.11.8

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1.【基础网络架构】（WACV2024）SBCFormer: Lightweight Network Capable of Full-size ImageNet Classification at 1 FPS on Single Board Computers

• 论文地址：https://arxiv.org//pdf/2311.03747

• 开源代码：GitHub - xyongLu/SBCFormer: SBCFormer: Lightweight Network Capable of Full-size ImageNet Classification at 1 FPS on Single Board Computers - WACV2024

2.【基础网络架构：Transformer】FLORA: Fine-grained Low-Rank Architecture Search for Vision Transformer

• 论文地址：https://arxiv.org//pdf/2311.03912

• 开源代码：GitHub - shadowpa0327/FLORA

3.【基础网络架构：Transformer】Mini but Mighty: Finetuning ViTs with Mini Adapters

• 论文地址：https://arxiv.org//pdf/2311.03873

• 开源代码（即将开源）：GitHub - IemProg/MiMi: Mini but Mighty: Finetuning ViTs with Mini Adapters

4.【图像分类】A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis

• 论文地址：https://arxiv.org//pdf/2311.04157

• 开源代码：GitHub - Imageomics/INTR: This is an official implementation for INTR: Interpretable Transformer for Fine-grained Image Classification

5.【异常检测】Image-Pointcloud Fusion based Anomaly Detection using PD-REAL Dataset

• 论文地址：https://arxiv.org//pdf/2311.04095

• 开源代码（即将开源）：GitHub - Andy-cs008/PD-REAL

6.【车道线检测】Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps

• 论文地址：https://arxiv.org//pdf/2311.04079

• 开源代码（即将开源）：https://github.com/NVlabs/SMERF

7.【3D目标检测】mmFUSION: Multimodal Fusion for 3D Objects Detection

• 论文地址：https://arxiv.org//pdf/2311.04058

• 代码即将开源

8.【行人重识别】Multi-view Information Integration and Propagation for Occluded Person Re-identification

• 论文地址：https://arxiv.org//pdf/2311.03828

• 开源代码：GitHub - nengdong96/MVIIP

9.【多模态】OtterHD: A High-Resolution Multi-modality Model

• 论文地址：https://arxiv.org//pdf/2311.04219

• 开源代码：GitHub - Luodian/Otter: 🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.

10.【多模态】（WACV2024）Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining

• 论文地址：https://arxiv.org//pdf/2311.03964

• 工程主页：Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining

• 开源代码：GitHub - ugorsahin/Generative-Negative-Mining: Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining, WACV 2024

11.【多任务学习】Data exploitation: multi-task learning of object detection and semantic segmentation on partially annotated data

• 论文地址：https://arxiv.org//pdf/2311.04040

• 开源代码（即将开源）：https://github.com/lhoangan/multas

12.【Diffusion】I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models

• 论文地址：https://arxiv.org//pdf/2311.04145

• 工程主页：I2VGen-XL

• 开源代码：GitHub - damo-vilab/i2vgen-xl: Official repo for I2VGen-XL: High-Quality Image-to-Video Synthesis Via Cascaded Diffusion Models

13.【NeRF】UP-NeRF: Unconstrained Pose-Prior-Free Neural Radiance Fields

• 论文地址：https://arxiv.org//pdf/2311.03784

• 开源代码（即将开源）：https://github.com/mlvlab/UP-NeRF

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