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

https://github.com/sshkhr/BigDataCup18_Submission

공식 코드

Road Damage Detection And Classification In Smartphone Captured Images Using Mask R-CNN

https://github.com/ssloxford/short-lived-adversarial-perturbations

공식 코드

SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial Perturbations

https://github.com/ssloxford/they-see-me-rollin

공식 코드

They See Me Rollin': Inherent Vulnerability of the Rolling Shutter in CMOS Image Sensors

https://github.com/sssssuperior/vscode

공식 코드

VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning

https://github.com/sssste/react

공식 코드

ReAct: Temporal Action Detection with Relational Queries

https://github.com/ssyc123/gsnet

공식 코드

Learning to Reduce Information Bottleneck for Object Detection in Aerial Images

https://github.com/stanfordmimi/villa

공식 코드

ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data

https://github.com/stardist/stardist

공식 코드

Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy

https://github.com/startracker0/physaug

공식 코드

PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection

https://github.com/stella-von/LKDN

공식 코드

Large Kernel Distillation Network for Efficient Single Image Super-Resolution

https://github.com/stella-von/MAT

공식 코드

MAT: Multi-Range Attention Transformer for Efficient Image Super-Resolution

https://github.com/stevekola/sign-to-speech-for-sign-language-understanding

공식 코드

Sign-to-Speech Model for Sign Language Understanding: A Case Study of Nigerian Sign Language

https://github.com/steven-lang/dafne

공식 코드

DAFNe: A One-Stage Anchor-Free Approach for Oriented Object Detection

https://github.com/stevengrove/vtpack

공식 코드

Dynamic Grained Encoder for Vision Transformers

https://github.com/stevenlauhkhk/large-separable-kernel-attention

공식 코드

Large Separable Kernel Attention: Rethinking the Large Kernel Attention Design in CNN

https://github.com/stevetsui/ida-det

공식 코드

IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors

https://github.com/stevetsui/q-detr

공식 코드

Q-DETR: An Efficient Low-Bit Quantized Detection Transformer

https://github.com/stevetsui/rbonn

공식 코드

Recurrent Bilinear Optimization for Binary Neural Networks

https://github.com/stevewongv/sparse2dense

공식 코드

Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection

https://github.com/sthalles/clove

공식 코드

Self-supervised Learning of Contextualized Local Visual Embeddings

https://github.com/stiphyjay/lidar-ptq

공식 코드

LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection

https://github.com/stogiannidis/srbench

공식 코드

Mind the Gap: Benchmarking Spatial Reasoning in Vision-Language Models

https://github.com/stormyoung/PRAI-1581

공식 코드

Person Re-identification in Aerial Imagery

https://github.com/storymy/take-off-eyeglasses

공식 코드

Portrait Eyeglasses and Shadow Removal by Leveraging 3D Synthetic Data

https://github.com/striveagain/megasr

공식 코드

MegaSR: Mining Customized Semantics and Expressive Guidance for Image Super-Resolution

https://github.com/strongwolf/dw

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A Dual Weighting Label Assignment Scheme for Object Detection

https://github.com/sty61010/crossdtr

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CrossDTR: Cross-view and Depth-guided Transformers for 3D Object Detection

https://github.com/subeeshvasu/2018_subeesh_epsr_eccvw

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Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network

https://github.com/subeeshvasu/Awesome-Deblurring

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Blind Image Deblurring with Unknown Kernel Size and Substantial Noise

https://github.com/sudo-Boris/mr-Blip

공식 코드

The Surprising Effectiveness of Multimodal Large Language Models for Video Moment Retrieval

https://github.com/suhaisheng/robosense

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RoboSense: Large-scale Dataset and Benchmark for Egocentric Robot Perception and Navigation in Crowded and Unstructured Environments

https://github.com/sullichrosu/njobvu-ai

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Njobvu-AI: An open-source tool for collaborative image labeling and implementation of computer vision models

https://github.com/sumanyumuku98/contextual-bias

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Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias

https://github.com/sun1992/hpun

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Hybrid Pixel-Unshuffled Network for Lightweight Image Super-Resolution

https://github.com/sunanhe/mkt

공식 코드

Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer

https://github.com/sunh18/monosim

공식 코드

MonoSIM: Simulating Learning Behaviors of Heterogeneous Point Cloud Object Detectors for Monocular 3D Object Detection

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