lanace_lana测试

编辑丨极市平台CVPR2023已经放榜，今年有2360篇，接收率为25.78%。在CVPR2023正式会议召开前，为了让大家更快地获取和学习到计

 

编辑丨极市平台CVPR2023已经放榜，今年有2360篇，接收率为25.78%在CVPR2023正式会议召开前，为了让大家更快地获取和学习到计算机视觉前沿技术，极市对CVPR2023 最新论文进行追踪，包括分研究方向的论文、代码汇总以及论文技术直播分享。

CVPR 2023 论文分方向整理目前在极市社区持续更新中，已累计更新了381篇，项目地址：https://www.cvmart.net/community/detail/7422以下是最近更新的 CVPR 2023 论文，包含检测、分割、人脸、视频处理、医学影像、神经网络结构、多模态、小样本学习等方向。

下载地址：https://www.cvmart.net/community/detail/7456目录- 检测 - 分割 - 视频处理 - 估计 - 人脸 - 目标跟踪 - 图像&视频检索/视频理解 - 医学影像 - GAN/生成式/对抗式 - 图像生成/图像合成 - 神经网络结构设计 - 数据处理 - 模型训练/泛化 - 图像特征提取与匹配 - 视觉表征学习 - 模型评估 - 多模态学习 - 视觉预测 - 数据集 - 小样本学习/零样本学习 - 持续学习 - 迁移学习/domain/自适应 - 场景图 - 视觉定位/位姿估计 - 视觉推理/视觉问答 - 对比学习 - 强化学习 - 机器人 - 半监督学习/弱监督学习/无监督学习/自监督学习 - 其他

检测2D 目标检测(2D Object Detection)[1]Object-Aware Distillation Pyramid for Open-Vocabulary Object Detection

paper：https://arxiv.org/abs/2303.058923D 目标检测(3D object detection)[1]Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection

paper：https://arxiv.org/abs/2303.05886[2]PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D Object Detection

paper：https://arxiv.org/abs/2303.08129code：https://github.com/blvlab/pimae

[3]MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequencespaper：https://arxiv.org/abs/2303.08316

[4]CAPE: Camera View Position Embedding for Multi-View 3D Object Detectionpaper：https://arxiv.org/abs/2303.10209

code：https://github.com/PaddlePaddle/Paddle3D[5]Weakly Supervised Monocular 3D Object Detection using Multi-View Projection and Direction Consistency

paper：https://arxiv.org/abs/2303.08686)[6]AeDet: Azimuth-invariant Multi-view 3D Object Detectionpaper：https://arxiv.org/abs/2211.12501

code：https://github.com/fcjian/AeDet异常检测(Anomaly Detection)[1]DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection

paper：https://arxiv.org/abs/2211.11317分割全景分割(Panoptic Segmentation)[1]UniDAformer: Unified Domain Adaptive Panoptic Segmentation Transformer via Hierarchical Mask Calibration

paper：https://arxiv.org/abs/2206.15083

语义分割(Semantic Segmentation)[1]MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Drivingpaper：https://arxiv.org/abs/2303.08600

code：https://github.com/jialeli1/lidarseg3d[2]Side Adapter Network for Open-Vocabulary Semantic Segmentation

paper：https://arxiv.org/abs/2302.12242code：https://github.com/mendelxu/san[3]Multi-view Inverse Rendering for Large-scale Real-world Indoor Scenes

paper：https://arxiv.org/abs/2211.10206实例分割(Instance Segmentation)[1]FastInst: A Simple Query-Based Model for Real-Time Instance Segmentation

paper：https://arxiv.org/abs/2303.08594[2]SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentation

paper：https://arxiv.org/abs/2303.08578code：https://github.com/lslrh/sim[3]DynaMask: Dynamic Mask Selection for Instance Segmentation

paper：https://arxiv.org/abs/2303.07868code：https://github.com/lslrh/dynamask视频目标分割(Video Object Segmentation)

[1]MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillationpaper：https://arxiv.org/abs/2303.07815

[2]InstMove: Instance Motion for Object-centric Video Segmentationpaper：https://arxiv.org/abs/2303.08132

code：https://github.com/wjf5203/vnext

[3]Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentationpaper：https://arxiv.org/abs/2303.10100

视频处理(Video Processing)[1]MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation

paper：https://arxiv.org/abs/2303.07815[2]InstMove: Instance Motion for Object-centric Video Segmentation

paper：https://arxiv.org/abs/2303.08132code：https://github.com/wjf5203/vnext[3]Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Prior

paper：https://arxiv.org/abs/2303.09757code：https://github.com/jiaqixuac/map-net[4]Blind Video Deflickering by Neural Filtering with a Flawed Atlas

paper：https://arxiv.org/abs/2303.08120code：https://github.com/chenyanglei/all-in-one-deflicker视频生成/视频合成(Video Generation/Video Synthesis)

[1]3D Cinemagraphy from a Single Imagepaper：https://arxiv.org/abs/2303.05724[2]VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

paper：https://arxiv.org/abs/2303.08320code：https://github.com/modelscope/modelscope视频超分(Video Super-Resolution)

[1]Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfittingpaper：https://arxiv.org/abs/2303.08331

估计光流/运动估计(Optical Flow/Motion Estimation)[1]Rethinking Optical Flow from Geometric Matching Consistent Perspective

paper：https://arxiv.org/abs/2303.08384code：https://github.com/dqiaole/matchflow深度估计(Depth Estimation)

[1]Fully Self-Supervised Depth Estimation from Defocus Cluepaper：https://arxiv.org/abs/2303.10752code：https://github.com/ehzoahis/dered

人体解析/人体姿态估计(Human Parsing/Human Pose Estimation)[1]Mutual Information-Based Temporal Difference Learning for Human Pose Estimation in Video

paper：https://arxiv.org/abs/2303.08475[2]Markerless Camera-to-Robot Pose Estimation via Self-supervised Sim-to-Real Transfer

paper：https://arxiv.org/abs/2302.14338手势估计(Gesture Estimation)[1]CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment

paper：https://arxiv.org/abs/2303.05725code：https://arxiv.org/abs/2303.05725图像处理[1]DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulation

paper：https://arxiv.org/abs/2303.06285code：https://github.com/yueming6568/deltaedit图像复原/图像增强/图像重建(Image Restoration/Image Reconstruction)

[1]Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bankpaper：https://arxiv.org/abs/2303.09101

code：https://github.com/huang-shirui/semi-uir[1]ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction

paper：https://arxiv.org/abs/2303.05938code：https://github.com/zhengdiyu/arbitrary-hands-3d-reconstruction

风格迁移(Style Transfer)[1]StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fieldspaper：https://arxiv.org/abs/2303.10598

[2]Fix the Noise: Disentangling Source Feature for Transfer Learning of StyleGANpaper：https://arxiv.org/abs/2204.14079

code：https://github.com/LeeDongYeun/FixNoise人脸人脸识别/检测(Facial Recognition/Detection)[1]Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detection

paper：https://arxiv.org/abs/2303.08545[2]Multi Modal Facial Expression Recognition with Transformer-Based Fusion Networks and Dynamic Sampling

paper：https://arxiv.org/abs/2303.08419人脸生成/合成/重建/编辑(Face Generation/Face Synthesis/Face Reconstruction/Face Editing)

[1]Robust Model-based Face Reconstruction through Weakly-Supervised Outlier Segmentationpaper：https://arxiv.org/abs/2106.09614

code：https://github.com/unibas-gravis/Occlusion-Robust-MoFA目标跟踪(Object Tracking)[1]MotionTrack: Learning Robust Short-term and Long-term Motions for Multi-Object Tracking

paper：https://arxiv.org/abs/2303.10404[2]Visual Prompt Multi-Modal Trackingpaper：https://arxiv.org/abs/2303.10826

code：https://github.com/jiawen-zhu/vipt图像&视频检索/视频理解(Image&Video Retrieval/Video Understanding)[1]Data-Free Sketch-Based Image Retrieval

paper：https://arxiv.org/abs/2303.07775[2]DAA: A Delta Age AdaIN operation for age estimation via binary code transformer

paper：https://arxiv.org/abs/2303.07929[3]Dual-path Adaptation from Image to Video Transformerspaper：https://arxiv.org/abs/2303.09857

code：https://github.com/park-jungin/dualpath图像/视频字幕(Image/Video Caption)[1]Dual-Stream Transformer for Generic Event Boundary Captioning

paper：https://arxiv.org/abs/2207.03038code：https://github.com/gx77/dual-stream-transformer-for-generic-event-boundary-captioning

行为识别/动作识别/检测/分割/定位(Action/Activity Recognition)[1]Video Test-Time Adaptation for Action Recognitionpaper：https://arxiv.org/abs/2211.15393

行人重识别/检测(Re-Identification/Detection)[1]TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning with Structure-Trajectory Prompted Reconstruction for Person Re-Identification

paper：https://arxiv.org/abs/2303.06819code：https://github.com/kali-hac/transg医学影像(Medical Imaging)[1]Neuron Structure Modeling for Generalizable Remote Physiological Measurement

paper：https://arxiv.org/abs/2303.05955code：https://github.com/lupaopao/nest

[2]Unsupervised Contour Tracking of Live Cells by Mechanical and Cycle Consistency Lossespaper：https://arxiv.org/abs/2303.08364

code：https://github.com/junbongjang/contour-tracking[3]Task-specific Fine-tuning via Variational Information Bottleneck for Weakly-supervised Pathology Whole Slide Image Classification

paper：https://arxiv.org/abs/2303.08446GAN/生成式/对抗式(GAN/Generative/Adversarial)[2]Graph Transformer GANs for Graph-Constrained House Generation

paper：https://arxiv.org/abs/2303.08225[1]Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models

paper：https://arxiv.org/abs/2303.10774图像生成/图像合成(Image Generation/Image Synthesis)[1]3DQD: Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process

paper：https://arxiv.org/abs/2303.10406code：https://github.com/colorful-liyu/3dqd[2]A Dynamic Multi-Scale Voxel Flow Network for Video Prediction

paper：https://arxiv.org/abs/2303.09875code：https://github.com/megvii-research/CVPR2023-DMVFN[3]Regularized Vector Quantization for Tokenized Image Synthesis

paper：https://arxiv.org/abs/2303.06424三维视觉点云(Point Cloud)[1]Controllable Mesh Generation Through Sparse Latent Point Diffusion Models

paper：https://arxiv.org/abs/2303.07938[2]Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis

paper：https://arxiv.org/abs/2303.08134code：https://github.com/zrrskywalker/point-nn[3]Rotation-Invariant Transformer for Point Cloud Matching

paper：https://arxiv.org/abs/2303.08231[4]Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration

paper：https://arxiv.org/abs/2303.09950code：https://github.com/qinzheng93/graphscnet三维重建(3D Reconstruction)

[1]Masked Wavelet Representation for Compact Neural Radiance Fieldspaper：https://arxiv.org/abs/2212.09069

[2]Decoupling Human and Camera Motion from Videos in the Wildpaper：https://arxiv.org/abs/2302.12827[3]Structural Multiplane Image: Bridging Neural View Synthesis and 3D Reconstruction

paper：https://arxiv.org/abs/2303.05937[4]NEF: Neural Edge Fields for 3D Parametric Curve Reconstruction from Multi-view Images

paper：https://arxiv.org/abs/2303.07653

[5]PartNeRF: Generating Part-Aware Editable 3D Shapes without 3D Supervisionpaper：https://arxiv.org/abs/2303.09554

[6]SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generationpaper：https://arxiv.org/abs/2212.04493

code：https://github.com/yccyenchicheng/SDFusion场景重建/视图合成/新视角合成(Novel View Synthesis)[1]Robust Dynamic Radiance Fields

paper：https://arxiv.org/abs/2301.02239[2]I2-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFs

paper：https://arxiv.org/abs/2303.07634[3]MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures

paper：https://arxiv.org/abs/2208.00277code：https://github.com/google-research/jax3d神经网络结构设计(Neural Network Structure Design)

[1]LargeKernel3D: Scaling up Kernels in 3D Sparse CNNspaper：https://arxiv.org/abs/2206.10555code：https://github.com/dvlab-research/largekernel3d

CNN[1]Randomized Adversarial Training via Taylor Expansionpaper：https://arxiv.org/abs/2303.10653code：https://github.com/alexkael/randomized-adversarial-training

[2]Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activationspaper：https://arxiv.org/abs/2303.08085

code：https://github.com/hmichaeli/alias_free_convnetsTransformer[1]BiFormer: Vision Transformer with Bi-Level Routing Attention

paper：https://arxiv.org/abs/2303.08810code：https://github.com/rayleizhu/biformer

[2]Making Vision Transformers Efficient from A Token Sparsification Viewpaper：https://arxiv.org/abs/2303.08685

图神经网络(GNN)[1]Turning Strengths into Weaknesses: A Certified Robustness Inspired Attack Framework against Graph Neural Networks

paper：https://arxiv.org/abs/2303.06199数据处理[1]TINC: Tree-structured Implicit Neural Compressionpaper：https://arxiv.org/abs/2211.06689

code：https://github.com/richealyoung/tinc图像聚类(Image Clustering)[1]On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering

paper：https://arxiv.org/abs/2303.09877code：https://github.com/danieltrosten/deepmvc模型训练/泛化(Model Training/Generalization)

[1]HumanBench: Towards General Human-centric Perception with Projector Assisted Pretrainingpaper：https://arxiv.org/abs/2303.05675

[2]Universal Instance Perception as Object Discovery and Retrievalpaper：https://arxiv.org/abs/2303.06674

code：https://github.com/MasterBin-IIAU/UNINEXT[3]Sharpness-Aware Gradient Matching for Domain Generalization

paper：https://arxiv.org/abs/2303.10353code：https://github.com/wang-pengfei/sagm图像特征提取与匹配(Image feature extraction and matching)

[2]Iterative Geometry Encoding Volume for Stereo Matchingpaper：https://arxiv.org/abs/2303.06615code：https://github.com/gangweix/igev

[1]Referring Image Mattingpaper：https://arxiv.org/abs/2206.05149code：https://github.com/jizhizili/rim

视觉表征学习(Visual Representation Learning)[1]MARLIN: Masked Autoencoder for facial video Representation LearnINg

paper：https://arxiv.org/abs/2211.06627code：https://github.com/ControlNet/MARLIN模型评估(Model Evaluation)

[1]TrojDiff: Trojan Attacks on Diffusion Models with Diverse Targetspaper：https://arxiv.org/abs/2303.05762

code：https://github.com/chenweixin107/trojdiff多模态学习(Multi-Modal Learning)[1]Mutilmodal Feature Extraction and Attention-based Fusion for Emotion Estimation in Videos

paper：https://arxiv.org/abs/2303.10421code：https://github.com/xkwangcn/abaw-5th-rt-iai[2]Emotional Reaction Intensity Estimation Based on Multimodal Data

paper：https://arxiv.org/abs/2303.09167[3]Multimodal Feature Extraction and Fusion for Emotional Reaction Intensity Estimation and Expression Classification in Videos with Transformers

paper：https://arxiv.org/abs/2303.09164[4]Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning

paper：https://arxiv.org/abs/2303.05952视听学习(Audio-visual Learning)[1]Watch or Listen: Robust Audio-Visual Speech Recognition with Visual Corruption Modeling and Reliability Scoring

paper：https://arxiv.org/abs/2303.08536code：https://github.com/joannahong/av-relscore

[2]CASP-Net: Rethinking Video Saliency Prediction from an Audio-VisualConsistency Perceptual Perspective

paper：https://arxiv.org/abs/2303.06357code：https://arxiv.org/abs/2303.06357视觉-语言（Vision-language）[1]Lana: A Language-Capable Navigator for Instruction Following and Generation

paper：https://arxiv.org/abs/2303.08409code：https://github.com/wxh1996/lana-vln视觉预测(Vision-based Prediction)

[1]TBP-Former: Learning Temporal Birds-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving

paper：https://arxiv.org/abs/2303.09998数据集(Dataset)[1]A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others

paper：https://arxiv.org/abs/2212.04825code：https://github.com/facebookresearch/Whac-A-Mole[2]MVImgNet: A Large-scale Dataset of Multi-view Images

paper：https://arxiv.org/abs/2303.06042[3]SLOPER4D: A Scene-Aware Dataset for Global 4D Human Pose Estimation in Urban Environments

paper：https://arxiv.org/abs/2303.09095code：https://github.com/climbingdaily/SLOPER4D[4]A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others

paper：https://arxiv.org/abs/2212.04825code：https://github.com/facebookresearch/Whac-A-Mole[5]MVImgNet: A Large-scale Dataset of Multi-view Images

paper：https://arxiv.org/abs/2303.06042小样本学习/零样本学习(Few-shot Learning/Zero-shot Learning)[1]DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object Detection

paper：https://arxiv.org/abs/2303.09674code：https://github.com/phoenix-v/digeo[2]Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings

paper：https://arxiv.org/abs/2303.09352code：https://github.com/uitml/nohub[3]Bi-directional Distribution Alignment for Transductive Zero-Shot Learning

paper：https://arxiv.org/abs/2303.08698code：https://github.com/zhicaiwww/bi-vaegan持续学习(Continual Learning/Life-long Learning)

[1]Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learningpaper：https://arxiv.org/abs/2303.09483

code：https://github.com/kim-sanghwan/ancl迁移学习/domain/自适应(Transfer Learning/Domain Adaptation)[1]Trainable Projected Gradient Method for Robust Fine-tuning

paper：https://arxiv.org/abs/2303.10720[2]DA-DETR: Domain Adaptive Detection Transformer with Information Fusion

paper：https://arxiv.org/abs/2103.17084[3]Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection

paper：https://arxiv.org/abs/2203.15793code：https://github.com/vibashan/irg-sfda

[4]Instance Relation Graph Guided Source-Free Domain Adaptive Object Detectionpaper：https://arxiv.org/abs/2203.15793

code：https://github.com/vibashan/irg-sfda场景图场景图理解(Scene Graph Understanding)[1]PLA: Language-Driven Open-Vocabulary 3D Scene Understanding

paper：https://arxiv.org/abs/2211.16312code：https://github.com/cvmi-lab/pla视觉定位/位姿估计(Visual Localization/Pose Estimation)

[1]PSVT: End-to-End Multi-person 3D Pose and Shape Estimation with Progressive Video Transformerspaper：https://arxiv.org/abs/2303.09187

[2]StructVPR: Distill Structural Knowledge with Weighting Samples for Visual Place Recognitionpaper：https://arxiv.org/abs/2212.00937

视觉推理/视觉问答(Visual Reasoning/VQA)[1]Divide and Conquer: Answering Questions with Object Factorization and Compositional Reasoning

paper：https://arxiv.org/abs/2303.10482code：https://github.com/szzexpoi/poem[2]Generative Bias for Robust Visual Question Answering

paper：https://arxiv.org/abs/2208.00690对比学习(Contrastive Learning)[1]Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report Generation

paper：https://arxiv.org/abs/2303.10323code：https://github.com/mlii0117/dcl强化学习(Reinforcement Learning)

[1]EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoningpaper：https://arxiv.org/abs/2303.10876

code：https://github.com/mediabrain-sjtu/eqmotion机器人(Robotic)[1]Efficient Map Sparsification Based on 2D and 3D Discretized Grids

paper：https://arxiv.org/abs/2303.10882半监督学习/弱监督学习/无监督学习/自监督学习(Self-supervised Learning/Semi-supervised Learning)

[1]Extracting Class Activation Maps from Non-Discriminative Features as wellpaper：https://arxiv.org/abs/2303.10334

code：https://github.com/zhaozhengchen/lpcam

[2]TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentationpaper：https://arxiv.org/abs/2303.09870

code：https://github.com/devavrattomar/tesla[3]LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding

paper：https://arxiv.org/abs/2303.09665[4]MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection

paper：https://arxiv.org/abs/2303.09061code：https://github.com/lliuz/mixteacher[5]Semi-supervised Hand Appearance Recovery via Structure Disentanglement and Dual Adversarial Discrimination

paper：https://arxiv.org/abs/2303.06380[6]Non-Contrastive Unsupervised Learning of Physiological Signals from Video

paper：https://arxiv.org/abs/2303.07944其他[1]Facial Affective Analysis based on MAE and Multi-modal Information for 5th ABAW Competition

paper：https://arxiv.org/abs/2303.10849[2]Partial Network Cloningpaper：https://arxiv.org/abs/2303.10597

code：https://github.com/jngwenye/pncloning[3]Uncertainty-Aware Optimal Transport for Semantically Coherent Out-of-Distribution Detection

paper：https://arxiv.org/abs/2303.10449code：https://github.com/lufan31/et-ood[4]Adversarial Counterfactual Visual Explanations

paper：https://arxiv.org/abs/2303.09962code：https://github.com/guillaumejs2403/ace[5]A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain Adaptation

paper：https://arxiv.org/abs/2303.09165code：https://github.com/huitangtang/on_the_utility_of_synthetic_data

[6]Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generationpaper：https://arxiv.org/abs/2303.09119

code：https://github.com/advocate99/diffgesture[7]Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry

paper：https://arxiv.org/abs/2303.08658code：https://github.com/kebii/r2et[8]Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations

paper：https://arxiv.org/abs/2202.04235code：https://github.com/twweeb/composite-adv[9]Backdoor Defense via Deconfounded Representation Learning

paper：https://arxiv.org/abs/2303.06818code：https://github.com/zaixizhang/cbd[10]Label Information Bottleneck for Label Enhancement

paper：https://arxiv.org/abs/2303.06836[11]LayoutDM: Discrete Diffusion Model for Controllable Layout Generation

paper：https://arxiv.org/abs/2303.08137code：https://github.com/CyberAgentAILab/layout-dm[12]Diversity-Aware Meta Visual Prompting

paper：https://arxiv.org/abs/2303.08138code：https://github.com/shikiw/dam-vp

免责声明：本站所有信息均搜集自互联网，并不代表本站观点，本站不对其真实合法性负责。如有信息侵犯了您的权益，请告知，本站将立刻处理。联系QQ：1640731186