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2D Classification

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

https://github.com/csl-ku/valo

공식 코드

VALO: A Versatile Anytime Framework for LiDAR-based Object Detection Deep Neural Networks

https://github.com/cstevenson-uva/creAI-gpt3

공식 코드

Putting GPT-3's Creativity to the (Alternative Uses) Test

https://github.com/csuhan/ReDet

공식 코드

ReDet: A Rotation-equivariant Detector for Aerial Object Detection

https://github.com/csuhan/opendet2

공식 코드

Expanding Low-Density Latent Regions for Open-Set Object Detection

https://github.com/csuhan/s2anet

공식 코드

Align Deep Features for Oriented Object Detection

https://github.com/csuhan/vfa

공식 코드

Few-Shot Object Detection via Variational Feature Aggregation

https://github.com/csuvis/BarchartReverseEngineering

공식 코드

Reverse-engineering Bar Charts Using Neural Networks

https://github.com/csysi/fsel

공식 코드

Frequency-Spatial Entanglement Learning for Camouflaged Object Detection

https://github.com/csysi/glconet

공식 코드

GLCONet: Learning Multi-source Perception Representation for Camouflaged Object Detection

https://github.com/csysi/udcnet

공식 코드

United Domain Cognition Network for Salient Object Detection in Optical Remote Sensing Images

https://github.com/cszcwu/gkmnet

공식 코드

Gaussian Kernel Mixture Network for Single Image Defocus Deblurring

https://github.com/cszhilu1998/bracketire

공식 코드

Exposure Bracketing Is All You Need For A High-Quality Image

https://github.com/cszhilu1998/selfir

공식 코드

Self-Supervised Image Restoration with Blurry and Noisy Pairs

https://github.com/cszn/DPIR

공식 코드

Plug-and-Play Image Restoration with Deep Denoiser Prior

https://github.com/cszn/DPSR

공식 코드

Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels

https://github.com/cszn/ircnn

공식 코드

Learning Deep CNN Denoiser Prior for Image Restoration

https://github.com/cszzshi/SimD

공식 코드

Similarity Distance-Based Label Assignment for Tiny Object Detection

https://github.com/ctu-vras/pcl-augmentation

공식 코드

Real3D-Aug: Point Cloud Augmentation by Placing Real Objects with Occlusion Handling for 3D Detection and Segmentation

https://github.com/ctu-vras/t-concord3d

공식 코드

Teachers in concordance for pseudo-labeling of 3D sequential data

https://github.com/ctuning/cbench

공식 코드

The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps

https://github.com/cty1934/efsa

공식 코드

EFSA: Towards Event-Level Financial Sentiment Analysis

https://github.com/cuibaby/dpk

공식 코드

Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation

https://github.com/cuiziteng/eccv_aeris

공식 코드

Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection

https://github.com/cuiziteng/iccv_maet

공식 코드

Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection

https://github.com/cuiziteng/illumination-adaptive-transformer

공식 코드

You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction

https://github.com/cuiziteng/maet

공식 코드

Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection

https://github.com/cunningham-lab/cb_and_cc

공식 코드

The continuous categorical: a novel simplex-valued exponential family

https://github.com/cuogeihong/ceasc

공식 코드

Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images

https://github.com/cuong-pv/FAM-KD

공식 코드

Frequency Attention for Knowledge Distillation

https://github.com/cuppp1998/360_object_tracking

공식 코드

Multiple Object Detection and Tracking in Panoramic Videos for Cycling Safety Analysis

https://github.com/currentf/hrn

공식 코드

Multi-Defendant Legal Judgment Prediction via Hierarchical Reasoning

https://github.com/custommetrics-sst/sst_customevaluationmetrics

공식 코드

SST-EM: Advanced Metrics for Evaluating Semantic, Spatial and Temporal Aspects in Video Editing

https://github.com/cv-core/MIT-Driverless-CV-TrainingInfra

공식 코드

Accurate, Low-Latency Visual Perception for Autonomous Racing:Challenges, Mechanisms, and Practical Solutions

https://github.com/cv-zhangxin/akconv

공식 코드

LDConv: Linear deformable convolution for improving convolutional neural networks

https://github.com/cv-zhangxin/ldconv

공식 코드

LDConv: Linear deformable convolution for improving convolutional neural networks

https://github.com/cv516buaa/ov-vg

공식 코드

OV-VG: A Benchmark for Open-Vocabulary Visual Grounding

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