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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/hunto/maskd

공식 코드

Masked Distillation with Receptive Tokens

https://github.com/husseinmozannar/SOQAL

공식 코드

Neural Arabic Question Answering

https://github.com/hust-jy/dds3d

공식 코드

DDS3D: Dense Pseudo-Labels with Dynamic Threshold for Semi-Supervised 3D Object Detection

https://github.com/hust-slow/anomalyncd

공식 코드

AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios

https://github.com/hustgetlijun/RCAN

공식 코드

Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement

https://github.com/hustvl/LSFA

공식 코드

Real-Time and Accurate Object Detection in Compressed Video by Long Short-term Feature Aggregation

https://github.com/hustvl/MSG-Transformer

공식 코드

MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens

https://github.com/hustvl/QueryInst

공식 코드

Instances as Queries

https://github.com/hustvl/YOLOS

공식 코드

You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection

https://github.com/hustvl/azinorm

공식 코드

AziNorm: Exploiting the Radial Symmetry of Point Cloud for Azimuth-Normalized 3D Perception

https://github.com/hustvl/featurized-queryrcnn

공식 코드

Featurized Query R-CNN

https://github.com/hustvl/mim4d

공식 코드

MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation Learning

https://github.com/hustvl/mimdet

공식 코드

Unleashing Vanilla Vision Transformer with Masked Image Modeling for Object Detection

https://github.com/hustvl/pd-quant

공식 코드

PD-Quant: Post-Training Quantization based on Prediction Difference Metric

https://github.com/hustvl/sparseinst

공식 코드

Sparse Instance Activation for Real-Time Instance Segmentation

https://github.com/hustvl/vim

공식 코드

Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

https://github.com/hustvl/weaksam

공식 코드

WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition

https://github.com/hustvl/yolop

공식 코드

YOLOP: You Only Look Once for Panoptic Driving Perception

https://github.com/huuxiaobin/hitnet

공식 코드

High-resolution Iterative Feedback Network for Camouflaged Object Detection

https://github.com/huyvnphan/eccv2022-ribac

공식 코드

RIBAC: Towards Robust and Imperceptible Backdoor Attack against Compact DNN

https://github.com/huyvvo/bib

공식 코드

Active Learning Strategies for Weakly-supervised Object Detection

https://github.com/hvision-nku/camoformer

공식 코드

CamoFormer: Masked Separable Attention for Camouflaged Object Detection

https://github.com/hvision-nku/conv2former

공식 코드

Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition

https://github.com/hvxlab/hvdetfusion

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HVDetFusion: A Simple and Robust Camera-Radar Fusion Framework

https://github.com/hwang1996/Meta-Concepts-for-Video-Captioning

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Cross-Modal Graph with Meta Concepts for Video Captioning

https://github.com/hxzhong1997/fsba

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Few-Shot Backdoor Attacks on Visual Object Tracking

https://github.com/hy0523/mtnet

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Learning Motion and Temporal Cues for Unsupervised Video Object Segmentation

https://github.com/hybrinfox/ppn

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Exposing propaganda: an analysis of stylistic cues comparing human annotations and machine classification

https://github.com/hychaochao/chat-models-backdoor-attacking

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Exploring Backdoor Vulnerabilities of Chat Models

https://github.com/hyeon-jo/interchange-transfer-kd

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itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detection

https://github.com/hyeonseob-nam/Batch-Instance-Normalization

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Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks

https://github.com/hyeonwoocho7/Cell_Detection-MICCAI

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Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap

https://github.com/hyeonwoocho7/UDA-Cell-Detection

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Effective Pseudo-Labeling based on Heatmap for Unsupervised Domain Adaptation in Cell Detection

https://github.com/hyjhkoh/mgtanet

공식 코드

MGTANet: Encoding Sequential LiDAR Points Using Long Short-Term Motion-Guided Temporal Attention for 3D Object Detection

https://github.com/hynky1999/czech-news-classification-dataset

공식 코드

A Dataset and Strong Baselines for Classification of Czech News Texts

https://github.com/hyt35/prox-qn

공식 코드

Provably Convergent Plug-and-Play Quasi-Newton Methods

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