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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/TencentARC/PhotoMaker

공식 코드

PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding

https://github.com/TerenceCYJ/S2HAND

공식 코드

Model-based 3D Hand Reconstruction via Self-Supervised Learning

https://github.com/Tete-Xiao/ReSim

공식 코드

Region Similarity Representation Learning

https://github.com/The-FinAI/FinTagging

공식 코드

FinTagging: An LLM-ready Benchmark for Extracting and Structuring Financial Information

https://github.com/Thmen/EGVSR

공식 코드

Real-Time Super-Resolution System of 4K-Video Based on Deep Learning

https://github.com/TimoBolkart/voca

공식 코드

Capture, Learning, and Synthesis of 3D Speaking Styles

https://github.com/Tombs98/ALGNet

공식 코드

Learning Enriched Features via Selective State Spaces Model for Efficient Image Deblurring

https://github.com/Tombs98/CAPTNet

공식 코드

Prompt-based Ingredient-Oriented All-in-One Image Restoration

https://github.com/Tombs98/M3SNet

공식 코드

A Mountain-Shaped Single-Stage Network for Accurate Image Restoration

https://github.com/Tombs98/SU-Net

공식 코드

SU-Net: Pose estimation network for non-cooperative spacecraft on-orbit

https://github.com/TonyLianLong/LLM-groundedDiffusion

공식 코드

LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models

https://github.com/TotalVariation/Flattenet

공식 코드

FlatteNet: A Simple Versatile Framework for Dense Pixelwise Prediction

https://github.com/Totoro97/Vid2Curve

공식 코드

Vid2Curve: Simultaneous Camera Motion Estimation and Thin Structure Reconstruction from an RGB Video

https://github.com/ToyotaCRDL/Visual-Concept-Blending

공식 코드

Zero-Shot Visual Concept Blending Without Text Guidance

https://github.com/ToyotaResearchInstitute/simnet

공식 코드

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo

https://github.com/UMich-BipedLab/extrinsic_lidar_camera_calibration

공식 코드

Improvements to Target-Based 3D LiDAR to Camera Calibration

https://github.com/UMich-BipedLab/global_pose_estimation_for_optimal_shape

공식 코드

Optimal Target Shape for LiDAR Pose Estimation

https://github.com/UT-Mao/Initial-Noise-Construction

공식 코드

The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization

https://github.com/UZ-SLAMLab/DrunkardsOdometry

공식 코드

The Drunkard's Odometry: Estimating Camera Motion in Deforming Scenes

https://github.com/UditSinghParihar/RoRD

공식 코드

RoRD: Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching

https://github.com/Uehwan/SimVODIS

공식 코드

SimVODIS: Simultaneous Visual Odometry, Object Detection, and Instance Segmentation

https://github.com/Uehwan/VisionForPedestrian

공식 코드

A Real-Time Predictive Pedestrian Collision Warning Service for Cooperative Intelligent Transportation Systems Using 3D Pose Estimation

https://github.com/Unity-Technologies/AnthroNet

공식 코드

AnthroNet: Conditional Generation of Humans via Anthropometrics

https://github.com/Unity-Technologies/com.unity.cv.synthetichumans

공식 코드

AnthroNet: Conditional Generation of Humans via Anthropometrics

https://github.com/VCG-team/DiffSegmenter

공식 코드

Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter

https://github.com/VCL3D/StructureNet

공식 코드

Deep Soft Procrustes for Markerless Volumetric Sensor Alignment

https://github.com/VDIGPKU/GSTO

공식 코드

GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling

https://github.com/VIS4ROB-lab/covins

공식 코드

COVINS-G: A Generic Back-end for Collaborative Visual-Inertial SLAM

https://github.com/VITA-Group/NeuralLift-360

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NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views

https://github.com/VITA-Group/Sandwich-Batch-Normalization

공식 코드

Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity

https://github.com/VRU-intention/casr

공식 코드

Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation

https://github.com/Va6lue/BST-Badminton-Stroke-type-Transformer

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BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports

https://github.com/Varal7/blank_language_model

공식 코드

Blank Language Models

https://github.com/Vchitect/LaVie

공식 코드

LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

https://github.com/Vegetebird/MHFormer

공식 코드

MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation

https://github.com/Vegetebird/StridedTransformer-Pose3D

공식 코드

Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.