CVPR 2024 Papers and Open Source Projects Collection (Papers with Code)

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[CVPR 2024 Paper Open Source Directory]

• 3DGS(Gaussian Splatting)
• Avatars
• Backbone
• CLIP
• [MAE] (#MAE)
• Embodied AI
• GAN
• [GNN] (#GNN)
• Multimodal Large Language Model (MLLM)
• Large Language Model (LLM)
• NAS
• OCR
• NeRF
• DETR
• Prompt
• Diffusion Models
• ReID (Re-identification)
• Long-Tail
• Vision Transformer
• Vision-Language
• Self-supervised Learning
• Data Augmentation
• Object Detection
• Anomaly Detection
• Visual Tracking
• Semantic Segmentation
• Instance Segmentation
• Panoptic Segmentation
• Medical Image#MI
• Medical Image Segmentation
• Video Object Segmentation
• Video Instance Segmentation
• Referring Image Segmentation
• Image Matting
• Image Editing
• Low-level Vision
• Super-Resolution
• Denoising
• Deblur
• Autonomous Driving
• 3D Point Cloud
• 3D Object Detection (#3DOD)
• 3D Semantic Segmentation
• 3D Object Tracking
• 3D Semantic Scene Completion (#3DSSC)
• 3D Registration
• 3D Human Pose Estimation
• 3D Human Mesh Estimation
• Medical Image
• Image Generation
• Video Generation
• 3D Generation
• Video Understanding
• Action Detection
• Text Detection
• Knowledge Distillation (#KD)
• Model Pruning
• Image Compression
• 3D Reconstruction
• Depth Estimation
• Trajectory Prediction
• Lane Detection
• Image Captioning
• Visual Question Answering (VQA)
• Sign Language Recognition
• Video Prediction
• Novel View Synthesis (#NVS)
• Zero-Shot Learning (#ZSL)
• Stereo Matching
• Feature Matching
• Scene Graph Generation
• Implicit Neural Representations
• Image Quality Assessment (#IQA)
• Video Quality Assessment
• Datasets
• New Tasks
• Others

3DGS(Gaussian Splatting)

Scaffold-GS: Structured 3D Gaussians for View-Adaptive Rendering

• Homepage: https://city-super.github.io/scaffold-gs/
• Paper: https://arxiv.org/abs/2312.00109
• Code: https://github.com/city-super/Scaffold-GS

GPS-Gaussian: Generalizable Pixel-wise 3D Gaussian Splatting for Real-time Human Novel View Synthesis

• Homepage: https://shunyuanzheng.github.io/GPS-Gaussian
• Paper: https://arxiv.org/abs/2312.02155
• Code: https://github.com/ShunyuanZheng/GPS-Gaussian

GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussians

• Paper: https://arxiv.org/abs/2312.02134
• Code: https://github.com/huliangxiao/GaussianAvatar

GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splatting

• Paper: https://arxiv.org/abs/2311.14521
• Code: https://github.com/buaacyw/GaussianEditor

Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction

• Homepage: https://ingra14m.github.io/Deformable-Gaussians/
• Paper: https://arxiv.org/abs/2309.13101
• Code: https://github.com/ingra14m/Deformable-3D-Gaussians

SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes

• Homepage: https://yihua7.github.io/SC-GS-web/
• Paper: https://arxiv.org/abs/2312.14937
• Code: https://github.com/yihua7/SC-GS

Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis

• Homepage: https://oppo-us-research.github.io/SpacetimeGaussians-website/
• Paper: https://arxiv.org/abs/2312.16812
• Code: https://github.com/oppo-us-research/SpacetimeGaussians

DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization

• Homepage: https://fictionarry.github.io/DNGaussian/
• Paper: https://arxiv.org/abs/2403.06912
• Code: https://github.com/Fictionarry/DNGaussian

4D Gaussian Splatting for Real-Time Dynamic Scene Rendering

• Paper: https://arxiv.org/abs/2310.08528
• Code: https://github.com/hustvl/4DGaussians

GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models

• Paper: https://arxiv.org/abs/2310.08529
• Code: https://github.com/hustvl/GaussianDreamer

Avatars

GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussians

• Paper: https://arxiv.org/abs/2312.02134
• Code: https://github.com/huliangxiao/GaussianAvatar

Real-Time Simulated Avatar from Head-Mounted Sensors

• Homepage: https://www.zhengyiluo.com/SimXR/
• Paper: https://arxiv.org/abs/2403.06862

Backbone

RepViT: Revisiting Mobile CNN From ViT Perspective

• Paper: https://arxiv.org/abs/2307.09283
• Code: https://github.com/THU-MIG/RepViT

TransNeXt: Robust Foveal Visual Perception for Vision Transformers

• Paper: https://arxiv.org/abs/2311.17132
• Code: https://github.com/DaiShiResearch/TransNeXt

CLIP

Alpha-CLIP: A CLIP Model Focusing on Wherever You Want

• Paper: https://arxiv.org/abs/2312.03818
• Code: https://github.com/SunzeY/AlphaCLIP

FairCLIP: Harnessing Fairness in Vision-Language Learning

• Paper: https://arxiv.org/abs/2403.19949
• Code: https://github.com/Harvard-Ophthalmology-AI-Lab/FairCLIP

IT IS

Embodied AI

EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI

• Homepage: https://tai-wang.github.io/embodiedscan/
• Paper: https://arxiv.org/abs/2312.16170
• Code: https://github.com/OpenRobotLab/EmbodiedScan

MP5: A Multi-modal Open-ended Embodied System in Minecraft via Active Perception

• Homepage: https://iranqin.github.io/MP5.github.io/
• Paper: https://arxiv.org/abs/2312.07472
• Code: https://github.com/IranQin/MP5

LEMON: Learning 3D Human-Object Interaction Relation from 2D Images

• Paper: https://arxiv.org/abs/2312.08963
• Code: https://github.com/yyvhang/lemon_3d

THOUGH

OCR

An Empirical Study of Scaling Law for OCR

• Paper: https://arxiv.org/abs/2401.00028
• Code: https://github.com/large-ocr-model/large-ocr-model.github.io

ODM: A Text-Image Further Alignment Pre-training Approach for Scene Text Detection and Spotting

• Paper: https://arxiv.org/abs/2403.00303
• Code: https://github.com/PriNing/ODM

NeRF

PIE-NeRF🍕: Physics-based Interactive Elastodynamics with NeRF

• Paper: https://arxiv.org/abs/2311.13099
• Code: https://github.com/FYTalon/pienerf/

DETR

DETRs Beat YOLOs on Real-time Object Detection

• Paper: https://arxiv.org/abs/2304.08069
• Code: https://github.com/lyuwenyu/RT-DETR

Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

• Paper: https://arxiv.org/abs/2403.16131
• Code: https://github.com/xiuqhou/Salience-DETR

Prompt

Multimodal Large Language Model (MLLM)

mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration

• Paper: https://arxiv.org/abs/2311.04257
• Code: https://github.com/X-PLUG/mPLUG-Owl/tree/main/mPLUG-Owl2

Link-Context Learning for Multimodal LLMs

• Paper: https://arxiv.org/abs/2308.07891
• Code: https://github.com/isekai-portal/Link-Context-Learning/tree/main

OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation

• Paper: https://arxiv.org/abs/2311.17911
• Code: https://github.com/shikiw/OPERA

Making Large Multimodal Models Understand Arbitrary Visual Prompts

• Homepage: https://vip-llava.github.io/
• Paper: https://arxiv.org/abs/2312.00784

Pink: Unveiling the power of referential comprehension for multi-modal llms

• Paper: https://arxiv.org/abs/2310.00582
• Code: https://github.com/SY-Xuan/Pink

Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding

• Paper: https://arxiv.org/abs/2311.08046
• Code: https://github.com/PKU-YuanGroup/Chat-UniVi

OneLLM: One Framework to Align All Modalities with Language

• Paper: https://arxiv.org/abs/2312.03700
• Code: https://github.com/csuhan/OneLLM

Large Language Model (LLM)

VTimeLLM: Empower LLM to Grasp Video Moments

• Paper: https://arxiv.org/abs/2311.18445
• Code: https://github.com/huangb23/VTimeLLM

IN THE

ReID (Re-identification)

Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

• Paper: https://arxiv.org/abs/2403.10254
• Code: https://github.com/924973292/EDITOR

Noisy-Correspondence Learning for Text-to-Image Person Re-identification

• Paper: https://arxiv.org/abs/2308.09911

• Code : https://github.com/QinYang79/RDE

Diffusion Models

InstanceDiffusion: Instance-level Control for Image Generation

• Homepage: https://people.eecs.berkeley.edu/~xdwang/projects/InstDiff/

• Paper: https://arxiv.org/abs/2402.03290

• Code: https://github.com/frank-xwang/InstanceDiffusion

Residual Denoising Diffusion Models

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/nachifur/RDDM

DeepCache: Accelerating Diffusion Models for Free

• Paper: https://arxiv.org/abs/2312.00858
• Code: https://github.com/horseee/DeepCache

DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations

• Homepage: https://tianhao-qi.github.io/DEADiff/

• Paper: https://arxiv.org/abs/2403.06951

• Code: https://github.com/Tianhao-Qi/DEADiff_code

SVGDreamer: Text Guided SVG Generation with Diffusion Model

• Paper: https://arxiv.org/abs/2312.16476
• Code: https://ximinng.github.io/SVGDreamer-project/

InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model

• Paper: https://arxiv.org/abs/2312.05849
• Code: https://github.com/jiuntian/interactdiffusion

MMA-Diffusion: MultiModal Attack on Diffusion Models

• Paper: https://arxiv.org/abs/2311.17516
• Code: https://github.com/yangyijune/MMA-Diffusion

VMC: Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models

• Homeoage: https://video-motion-customization.github.io/
• Paper: https://arxiv.org/abs/2312.00845
• Code: https://github.com/HyeonHo99/Video-Motion-Customization

Vision Transformer

TransNeXt: Robust Foveal Visual Perception for Vision Transformers

• Paper: https://arxiv.org/abs/2311.17132
• Code: https://github.com/DaiShiResearch/TransNeXt

RepViT: Revisiting Mobile CNN From ViT Perspective

• Paper: https://arxiv.org/abs/2307.09283
• Code: https://github.com/THU-MIG/RepViT

A General and Efficient Training for Transformer via Token Expansion

• Paper: https://arxiv.org/abs/2404.00672
• Code: https://github.com/Osilly/TokenExpansion

Vision-Language

PromptKD: Unsupervised Prompt Distillation for Vision-Language Models

• Paper: https://arxiv.org/abs/2403.02781
• Code: https://github.com/zhengli97/PromptKD

FairCLIP: Harnessing Fairness in Vision-Language Learning

• Paper: https://arxiv.org/abs/2403.19949
• Code: https://github.com/Harvard-Ophthalmology-AI-Lab/FairCLIP

Object Detection

DETRs Beat YOLOs on Real-time Object Detection

• Paper: https://arxiv.org/abs/2304.08069
• Code: https://github.com/lyuwenyu/RT-DETR

Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation

• Paper: https://arxiv.org/abs/2312.01220
• Code: https://github.com/ZPDu/Boosting-Object-Detection-with-Zero-Shot-Day-Night-Domain-Adaptation

YOLO-World: Real-Time Open-Vocabulary Object Detection

• Paper: https://arxiv.org/abs/2401.17270
• Code: https://github.com/AILab-CVC/YOLO-World

Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

• Paper: https://arxiv.org/abs/2403.16131
• Code: https://github.com/xiuqhou/Salience-DETR

Anomaly Detection

Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection

• Paper: https://arxiv.org/abs/2310.12790
• Code: https://github.com/mala-lab/AHL

Object Tracking

Delving into the Trajectory Long-tail Distribution for Muti-object Tracking

• Paper: https://arxiv.org/abs/2403.04700
• Code: https://github.com/chen-si-jia/Trajectory-Long-tail-Distribution-for-MOT

Semantic Segmentation

Stronger, Fewer, & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation

• Paper: https://arxiv.org/abs/2312.04265
• Code: https://github.com/w1oves/Rein

SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation

• Paper: https://arxiv.org/abs/2311.15537
• Code: https://github.com/xb534/SED

Medical Image

Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology

• Paper: https://arxiv.org/abs/2402.17228
• Code: https://github.com/DearCaat/RRT-MIL

VoCo: A Simple-yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis

• Paper: https://arxiv.org/abs/2402.17300
• Code: https://github.com/Luffy03/VoCo

ChAda-ViT : Channel Adaptive Attention for Joint Representation Learning of Heterogeneous Microscopy Images

• Paper: https://arxiv.org/abs/2311.15264
• Code: https://github.com/nicoboou/chada_vit

Medical Image Segmentation

Autonomous Driving

UniPAD: A Universal Pre-training Paradigm for Autonomous Driving

• Paper: https://arxiv.org/abs/2310.08370
• Code: https://github.com/Nightmare-n/UniPAD

Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications

• Paper: https://arxiv.org/abs/2311.17663
• Code: https://github.com/haomo-ai/Cam4DOcc

Memory-based Adapters for Online 3D Scene Perception

• Paper: https://arxiv.org/abs/2403.06974
• Code: https://github.com/xuxw98/Online3D

Symphonize 3D Semantic Scene Completion with Contextual Instance Queries

• Paper: https://arxiv.org/abs/2306.15670
• Code: https://github.com/hustvl/Symphonies

A Real-world Large-scale Dataset for Roadside Cooperative Perception

• Paper: https://arxiv.org/abs/2403.10145
• Code: https://github.com/AIR-THU/DAIR-RCooper

Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving

• Paper: https://arxiv.org/abs/2403.07535
• Code: https://github.com/Junda24/AFNet

Traffic Scene Parsing through the TSP6K Dataset

• Paper: https://arxiv.org/pdf/2303.02835.pdf
• Code: https://github.com/PengtaoJiang/TSP6K

3D-Point-Cloud

3D Object Detection

PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection

• Paper: https://arxiv.org/abs/2312.08371
• Code: https://github.com/kuanchihhuang/PTT

UniMODE: Unified Monocular 3D Object Detection

• Paper: https://arxiv.org/abs/2402.18573

3D Semantic Segmentation

Image Editing

Edit One for All: Interactive Batch Image Editing

• Homepage: https://thaoshibe.github.io/edit-one-for-all
• Paper: https://arxiv.org/abs/2401.10219
• Code: https://github.com/thaoshibe/edit-one-for-all

Video Editing

MaskINT: Video Editing via Interpolative Non-autoregressive Masked Transformers

• Homepage: https://maskint.github.io

• Paper: https://arxiv.org/abs/2312.12468

Low-level Vision

Residual Denoising Diffusion Models

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/nachifur/RDDM

Boosting Image Restoration via Priors from Pre-trained Models

• Paper: https://arxiv.org/abs/2403.06793

Super-Resolution

SeD: Semantic-Aware Discriminator for Image Super-Resolution

• Paper: https://arxiv.org/abs/2402.19387
• Code: https://github.com/lbc12345/SeD

APISR: Anime Production Inspired Real-World Anime Super-Resolution

• Paper: https://arxiv.org/abs/2403.01598
• Code: https://github.com/Kiteretsu77/APISR

Denoising

Image Denoising

3D Human Pose Estimation

Hourglass Tokenizer for Efficient Transformer-Based 3D Human Pose Estimation

• Paper: https://arxiv.org/abs/2311.12028
• Code: https://github.com/NationalGAILab/HoT

Image Generation

InstanceDiffusion: Instance-level Control for Image Generation

• Homepage: https://people.eecs.berkeley.edu/~xdwang/projects/InstDiff/

• Paper: https://arxiv.org/abs/2402.03290

• Code: https://github.com/frank-xwang/InstanceDiffusion

ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations

• Homepage: https://eclipse-t2i.vercel.app/

• Paper: https://arxiv.org/abs/2312.04655

• Code: https://github.com/eclipse-t2i/eclipse-inference

Instruct-Imagen: Image Generation with Multi-modal Instruction

• Paper: https://arxiv.org/abs/2401.01952

Residual Denoising Diffusion Models

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/nachifur/RDDM

UniGS: Unified Representation for Image Generation and Segmentation

• Paper: https://arxiv.org/abs/2312.01985

Multi-Instance Generation Controller for Text-to-Image Synthesis

• Paper: https://arxiv.org/abs/2402.05408
• Code: https://github.com/limuloo/migc

SVGDreamer: Text Guided SVG Generation with Diffusion Model

• Paper: https://arxiv.org/abs/2312.16476
• Code: https://ximinng.github.io/SVGDreamer-project/

InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model

• Paper: https://arxiv.org/abs/2312.05849
• Code: https://github.com/jiuntian/interactdiffusion

Ranni: Taming Text-to-Image Diffusion for Accurate Prompt Following

• Paper: https://arxiv.org/abs/2311.17002
• Code: https://github.com/ali-vilab/Ranni

Video Generation

Vlogger: Make Your Dream A Vlog

• Paper: https://arxiv.org/abs/2401.09414
• Code: https://github.com/Vchitect/Vlogger

VBench: Comprehensive Benchmark Suite for Video Generative Models

• Homepage: https://vchitect.github.io/VBench-project/
• Paper: https://arxiv.org/abs/2311.17982
• Code: https://github.com/Vchitect/VBench

VMC: Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models

• Homeoage: https://video-motion-customization.github.io/
• Paper: https://arxiv.org/abs/2312.00845
• Code: https://github.com/HyeonHo99/Video-Motion-Customization

3D Generation

CityDreamer: Compositional Generative Model of Unbounded 3D Cities

• Homepage: https://haozhexie.com/project/city-dreamer/
• Paper: https://arxiv.org/abs/2309.00610
• Code: https://github.com/hzxie/city-dreamer

LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching

• Paper: https://arxiv.org/abs/2311.11284
• Code: https://github.com/EnVision-Research/LucidDreamer

Video Understanding

MVBench: A Comprehensive Multi-modal Video Understanding Benchmark

• Paper: https://arxiv.org/abs/2311.17005
• Code: https://github.com/OpenGVLab/Ask-Anything/tree/main/video_chat2

Knowledge Distillation

Logit Standardization in Knowledge Distillation

• Paper: https://arxiv.org/abs/2403.01427
• Code: https://github.com/sunshangquan/logit-standardization-KD

Efficient Dataset Distillation via Minimax Diffusion

• Paper: https://arxiv.org/abs/2311.15529
• Code: https://github.com/vimar-gu/MinimaxDiffusion

Stereo Matching

Neural Markov Random Field for Stereo Matching

• Paper: https://arxiv.org/abs/2403.11193
• Code: https://github.com/aeolusguan/NMRF

Scene Graph Generation

HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation

• Homepage: https://zhangce01.github.io/HiKER-SGG/
• Paper : https://arxiv.org/abs/2403.12033
• Code: https://github.com/zhangce01/HiKER-SGG

Video Quality Assessment

KVQ: Kaleidoscope Video Quality Assessment for Short-form Videos

• Homepage: https://lixinustc.github.io/projects/KVQ/

• Paper: https://arxiv.org/abs/2402.07220

• Code: https://github.com/lixinustc/KVQ-Challenge-CVPR-NTIRE2024

#Datasets

A Real-world Large-scale Dataset for Roadside Cooperative Perception

• Paper: https://arxiv.org/abs/2403.10145
• Code: https://github.com/AIR-THU/DAIR-RCooper

Traffic Scene Parsing through the TSP6K Dataset

• Paper: https://arxiv.org/pdf/2303.02835.pdf
• Code: https://github.com/PengtaoJiang/TSP6K

Others

Object Recognition as Next Token Prediction

• Paper: https://arxiv.org/abs/2312.02142
• Code: https://github.com/kaiyuyue/nxtp

ParameterNet: Parameters Are All You Need for Large-scale Visual Pretraining of Mobile Networks

• Paper: https://arxiv.org/abs/2306.14525
• Code: https://parameternet.github.io/

Seamless Human Motion Composition with Blended Positional Encodings

• Paper: https://arxiv.org/abs/2402.15509
• Code: https://github.com/BarqueroGerman/FlowMDM

LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning

• Homepage: https://ll3da.github.io/

• Paper: https://arxiv.org/abs/2311.18651

• Code: https://github.com/Open3DA/LL3DA

CLOVA: A Closed-LOop Visual Assistant with Tool Usage and Update

• Homepage: https://clova-tool.github.io/
• Paper: https://arxiv.org/abs/2312.10908

MoMask: Generative Masked Modeling of 3D Human Motions

• Paper: https://arxiv.org/abs/2312.00063
• Code: https://github.com/EricGuo5513/momask-codes

Amodal Ground Truth and Completion in the Wild

• Homepage: https://www.robots.ox.ac.uk/~vgg/research/amodal/
• Paper: https://arxiv.org/abs/2312.17247
• Code: https://github.com/Championchess/Amodal-Completion-in-the-Wild

Improved Visual Grounding through Self-Consistent Explanations

• Paper: https://arxiv.org/abs/2312.04554
• Code: https://github.com/uvavision/SelfEQ

ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object

• Homepage: https://chenshuang-zhang.github.io/imagenet_d/
• Paper: https://arxiv.org/abs/2403.18775
• Code: https://github.com/chenshuang-zhang/imagenet_d

Learning from Synthetic Human Group Activities

• Homepage: https://cjerry1243.github.io/M3Act/
• Paper https://arxiv.org/abs/2306.16772
• Code: https://github.com/cjerry1243/M3Act

A Cross-Subject Brain Decoding Framework

• Homepage: https://littlepure2333.github.io/MindBridge/
• Paper: https://arxiv.org/abs/2404.07850
• Code: https://github.com/littlepure2333/MindBridge

Multi-Task Dense Prediction via Mixture of Low-Rank Experts

• Paper : https://arxiv.org/abs/2403.17749
• Code: https://github.com/YuqiYang213/MLoRE

Contrastive Mean-Shift Learning for Generalized Category Discovery

• Homepage: https://postech-cvlab.github.io/cms/
• Paper: https://arxiv.org/abs/2404.09451
• Code: https://github.com/sua-choi/CMS