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泊头网站优化,学ui哪家培训机构好,北京代理记账公司电话,网页编辑简单分为网页美工编辑和精华置顶 墙裂推荐#xff01;小白如何1个月系统学习CV核心知识#xff1a;链接 点击CV计算机视觉#xff0c;关注更多CV干货 论文已打包#xff0c;点击进入—下载界面 点击加入—CV计算机视觉交流群 1.【基础网络架构】#xff08;NeurIPS2023#xff09;Fa… 精华置顶 墙裂推荐小白如何1个月系统学习CV核心知识链接 点击CV计算机视觉关注更多CV干货 论文已打包点击进入—下载界面 点击加入—CV计算机视觉交流群 1.【基础网络架构】NeurIPS2023Fast Trainable Projection for Robust Fine-Tuning 论文地址https://arxiv.org//pdf/2310.19182 开源代码GitHub - GT-RIPL/FTP: This repo hosts the code for the Fast Trainable Projection (FTP) project. 2.【基础网络架构Transformer】TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition 论文地址https://arxiv.org//pdf/2310.19380 开源代码即将开源GitHub - LMMMEng/TransXNet 3.【图像分类】NeurIPS2023Analyzing Vision Transformers for Image Classification in Class Embedding Space 论文地址https://arxiv.org//pdf/2310.18969 开源代码GitHub - martinagvilas/vit-cls_emb: Accompanying code for Analyzing Vision Tranformers in Class Embedding Space (NeurIPS 23) 4.【目标检测】RGB-X Object Detection via Scene-Specific Fusion Modules 论文地址https://arxiv.org//pdf/2310.19372 开源代码GitHub - dsriaditya999/RGBXFusion 5.【目标检测】A High-Resolution Dataset for Instance Detection with Multi-View Instance Capture 论文地址https://arxiv.org//pdf/2310.19257 开源代码GitHub - insdet/instance-detection 6.【目标检测】PrObeD: Proactive Object Detection Wrapper 论文地址https://arxiv.org//pdf/2310.18788 开源代码即将开源GitHub - vishal3477/Proactive-Object-Detection 7.【异常检测】Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly Detection 论文地址https://arxiv.org//pdf/2310.19070 开源代码即将开源GitHub - tzjtatata/Myriad: Open-sourced codes, IAD vision-language datasets and pre-trained checkpoints for Myriad. 8.【异常检测】AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection 论文地址https://arxiv.org//pdf/2310.18961 开源代码即将开源GitHub - zqhang/AnomalyCLIP 9.【语义分割】NeurIPS2023Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union 论文地址https://arxiv.org//pdf/2310.19252 开源代码GitHub - zifuwanggg/JDTLosses: Optimization with JDTLoss and Evaluation with Fine-grained mIoUs for Semantic Segmentation 10.【语义分割】NeurIPS2023Switching Temporary Teachers for Semi-Supervised Semantic Segmentation 论文地址https://arxiv.org//pdf/2310.18640 开源代码即将开源GitHub - naver-ai/dual-teacher: Official code for the NeurIPS 2023 paper Switching Temporary Teachers for Semi-Supervised Semantic Segmentation 11.【Open-Vocabulary Segmentation】NeurIPS2023Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation 论文地址https://arxiv.org//pdf/2310.19001 开源代码即将开源GitHub - Ferenas/PGSeg: This is the official code of Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation, Neurips23 12.【视频语义分割】NeurIPS2023Mask Propagation for Efficient Video Semantic Segmentation 论文地址https://arxiv.org//pdf/2310.18954 开源代码即将开源GitHub - ziplab/MPVSS 13.【超分辨率重建】NeurIPS2023Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction 论文地址https://arxiv.org//pdf/2310.19011 开源代码即将开源GitHub - DengZeshuai/SRTTA 14.【超分辨率重建】EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution 论文地址https://arxiv.org//pdf/2310.19288 开源代码即将开源GitHub - XY-boy/EDiffSR: EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution 15.【领域泛化】NeurIPS2023SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization 论文地址https://arxiv.org//pdf/2310.19795 开源代码即将开源GitHub - donghao51/SimMMDG: [NeurIPS 2023] SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization 16.【领域泛化】WACV2024Domain Generalisation via Risk Distribution Matching 论文地址https://arxiv.org//pdf/2310.18598 开源代码GitHub - nktoan/risk-distribution-matching: Here is the codebase for our accepted paper in the Research Track of WACV24 on Domain Generalization via Risk Distribution Matching. 17.【多模态】Harvest Video Foundation Models via Efficient Post-Pretraining 论文地址https://arxiv.org//pdf/2310.19554 开源代码GitHub - OpenGVLab/InternVideo: InternVideo: General Video Foundation Models via Generative and Discriminative Learning (https://arxiv.org/abs/2212.03191) 18.【多模态】IterInv: Iterative Inversion for Pixel-Level T2I Models 论文地址https://arxiv.org//pdf/2310.19540 开源代码即将开源GitHub - Tchuanm/IterInv: The official implement of IterInv: Iterative Inversion for Pixel-Level T2I Models. 19.【多模态】Generating Context-Aware Natural Answers for Questions in 3D Scenes 论文地址https://arxiv.org//pdf/2310.19516 开源代码即将开源GitHub - MunzerDw/Gen3DQA: My guided research project on 3D visual question answering at the lab of Prof. Dr. Niessner at Technical University of Munich. 20.【多模态】Text-to-3D with Classifier Score Distillation 论文地址https://arxiv.org//pdf/2310.19415 工程主页Classifier Score Distillation 代码即将开源 21.【多模态】Dynamic Task and Weight Prioritization Curriculum Learning for Multimodal Imagery 论文地址https://arxiv.org//pdf/2310.19109 开源代码GitHub - fualsan/DATWEP: Source code for the Dynamic Task and Weight Prioritization Curriculum Learning for Multimodal Imagery 22.【多模态】TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding 论文地址https://arxiv.org//pdf/2310.19060 开源代码GitHub - RenShuhuai-Andy/TESTA: [EMNLP 2023] TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding 23.【多模态】Customizing 360-Degree Panoramas through Text-to-Image Diffusion Models 论文地址https://arxiv.org//pdf/2310.18840 开源代码GitHub - littlewhitesea/StitchDiffusion: This is the official implementation of Customizing 360-Degree Panoramas through Text-to-Image Diffusion Models (WACV2024) 24.【多模态】ROME: Evaluating Pre-trained Vision-Language Models on Reasoning beyond Visual Common Sense 论文地址https://arxiv.org//pdf/2310.19301 开源代码即将开源GitHub - K-Square-00/ROME 25.【多模态】Apollo: Zero-shot MultiModal Reasoning with Multiple Experts 论文地址https://arxiv.org//pdf/2310.18369 开源代码GitHub - danielabd/Apollo-Cap: Style Controllable Zero-Shot Image-to-Text Generation 26.【自监督学习】Local-Global Self-Supervised Visual Representation Learning 论文地址https://arxiv.org//pdf/2310.18651 开源代码GitHub - alijavidani/Local_Global_Representation_Learning 27.【自监督学习】NeurIPS2023InstanT: Semi-supervised Learning with Instance-dependent Thresholds 论文地址https://arxiv.org//pdf/2310.18910 开源代码即将开源tmllab/2023_NeurIPS_InstanT · GitHub 28.【单目3D目标检测】ODM3D: Alleviating Foreground Sparsity for Enhanced Semi-Supervised Monocular 3D Object Detection 论文地址https://arxiv.org//pdf/2310.18620 开源代码即将开源https://github.com/arcaninez/odm3d 29.【自动驾驶协同感知】Dynamic V2X Autonomous Perception from Road-to-Vehicle Vision 论文地址https://arxiv.org//pdf/2310.19113 开源代码即将开源tjy1423317192/AP2VP · GitHub 30.【自动驾驶深度估计】NeurIPS2023Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes 论文地址https://arxiv.org//pdf/2310.18887 工程主页Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes 开源代码即将开源GitHub - YihongSun/Dynamo-Depth: [NeurIPS 2023] Fixing Unsupervised Depth Estimation for Dynamical Scenes 31.【图像编辑】EMNLP2023Learning to Follow Object-Centric Image Editing Instructions Faithfully 论文地址https://arxiv.org//pdf/2310.19145 开源代码GitHub - tuhinjubcse/FaithfulEdits_EMNLP2023: Code and Data for EMNLP 2023 paper Learning to Follow Object-Centric Image Editing Instructions Faithfully 32.【视频生成】VideoCrafter1: Open Diffusion Models for High-Quality Video Generation 论文地址https://arxiv.org//pdf/2310.19512 工程主页VideoCrafter1 开源代码GitHub - AILab-CVC/VideoCrafter: VideoCrafter1: Open Diffusion Models for High-Quality Video Generation 33.【知识蒸馏】One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation 论文地址https://arxiv.org//pdf/2310.19444 开源代码GitHub - Hao840/OFAKD 34.【Continual Learning】NeurIPS2023NPCL: Neural Processes for Uncertainty-Aware Continual Learning 论文地址https://arxiv.org//pdf/2310.19272 开源代码即将开源GitHub - srvCodes/NPCL 论文已打包下载链接 CV计算机视觉交流群 群内包含目标检测、图像分割、目标跟踪、Transformer、多模态、NeRF、GAN、缺陷检测、显著目标检测、关键点检测、超分辨率重建、SLAM、人脸、OCR、生物医学图像、三维重建、姿态估计、自动驾驶感知、深度估计、视频理解、行为识别、图像去雾、图像去雨、图像修复、图像检索、车道线检测、点云目标检测、点云分割、图像压缩、运动预测、神经网络量化、网络部署等多个领域的大佬不定期分享技术知识、面试技巧和内推招聘信息。 想进群的同学请添加微信号联系管理员PingShanHai666。添加好友时请备注学校/公司研究方向昵称。 推荐阅读 使用目标之间的先验关系提升目标检测器性能
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