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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/gt-salt/positive-frames

공식 코드

Inducing Positive Perspectives with Text Reframing

https://github.com/gtzly/FADNet

공식 코드

Monocular 3D Object Detection with Sequential Feature Association and Depth Hint Augmentation

https://github.com/guang-yng/completeOMR

공식 코드

Toward a More Complete OMR Solution

https://github.com/guangxinghan/fct

공식 코드

Few-Shot Object Detection with Fully Cross-Transformer

https://github.com/guangxinghan/meta-faster-r-cnn

공식 코드

Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment

https://github.com/guangyliu/EISL

공식 코드

Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation

https://github.com/guanlongzhao/dehaze

공식 코드

Improved Techniques for Learning to Dehaze and Beyond: A Collective Study

https://github.com/guanrunwei/asy-vrnet

공식 코드

ASY-VRNet: Waterway Panoptic Driving Perception Model based on Asymmetric Fair Fusion of Vision and 4D mmWave Radar

https://github.com/guanw-pku/oed

공식 코드

OED: Towards One-stage End-to-End Dynamic Scene Graph Generation

https://github.com/guanxiongsun/stpn

공식 코드

Spatio-temporal Prompting Network for Robust Video Feature Extraction

https://github.com/guanxiongsun/vfe.pytorch

공식 코드

MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection

https://github.com/gudgud96/music-fader-nets

공식 코드

Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling

https://github.com/gudovskiy/cflow-ad

공식 코드

CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows

https://github.com/gudovskiy/e2x

공식 코드

Explain to Fix: A Framework to Interpret and Correct DNN Object Detector Predictions

https://github.com/gudovskiy/fmap_compression

공식 코드

DNN Feature Map Compression using Learned Representation over GF(2)

https://github.com/guillermocarbajal/j-mkpd

공식 코드

Blind Motion Deblurring with Pixel-Wise Kernel Estimation via Kernel Prediction Networks

https://github.com/guillermocarbajal/segmentationbaseddeblurringdataset

공식 코드

Rethinking Motion Deblurring Training: A Segmentation-Based Method for Simulating Non-Uniform Motion Blurred Images

https://github.com/gujiaqivadin/HomographyLoss

공식 코드

Homography Loss for Monocular 3D Object Detection

https://github.com/guobaoxiao/comprompter

공식 코드

COMPrompter: reconceptualized segment anything model with multiprompt network for camouflaged object detection

https://github.com/guobaoxiao/dsam

공식 코드

Exploring Deeper! Segment Anything Model with Depth Perception for Camouflaged Object Detection

https://github.com/guotaowang/STVS

공식 코드

Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection

https://github.com/guotong1988/Automatic-Label-Error-Correction

공식 코드

The Re-Label Method For Data-Centric Machine Learning

https://github.com/guowei-cn/cca_ud-universal-training-level-defence

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Universal Detection of Backdoor Attacks via Density-based Clustering and Centroids Analysis

https://github.com/guoyaoshen/rnst-regularization_by_nst

공식 코드

Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited Data

https://github.com/guozix/tai-dpt

공식 코드

Texts as Images in Prompt Tuning for Multi-Label Image Recognition

https://github.com/guthasaibharathchandra/MAP-GA

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Inverse Problems with Diffusion Models: A MAP Estimation Perspective

https://github.com/gwenzhang/GGA

공식 코드

General Geometry-aware Weakly Supervised 3D Object Detection

https://github.com/gwenzhang/voxel-mamba

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Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection

https://github.com/gwxuan/tsp3d

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Text-guided Sparse Voxel Pruning for Efficient 3D Visual Grounding

https://github.com/gyauney/domain-specific-lexical-grounding

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Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents

https://github.com/gyguo/pixeldistillation

공식 코드

Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition

https://github.com/gyhandy/3d-copy-paste

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3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection

https://github.com/gyhandy/neural-sim-nerf

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Neural-Sim: Learning to Generate Training Data with NeRF

https://github.com/gyhandy/text2image-for-detection

공식 코드

Beyond Generation: Harnessing Text to Image Models for Object Detection and Segmentation

https://github.com/gyyang23/afpn

공식 코드

AFPN: Asymptotic Feature Pyramid Network for Object Detection

https://github.com/gzhu06/generativesourceseparation

공식 코드

Music Source Separation with Generative Flow

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