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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/sharat29ag/CDAL

공식 코드

Contextual Diversity for Active Learning

https://github.com/sharif-apu/darkdeblur

공식 코드

DarkDeblur: Learning single-shot image deblurring in low-light condition

https://github.com/sharpiless/cascadev-det

공식 코드

CascadeV-Det: Cascade Point Voting for 3D Object Detection

https://github.com/shashank140195/Biomedical_QA_Model

공식 코드

Top K Relevant Passage Retrieval for Biomedical Question Answering

https://github.com/shashankskagnihotri/benchmarking_reliability_generalization

공식 코드

SemSegBench & DetecBench: Benchmarking Reliability and Generalization Beyond Classification

https://github.com/shashankvkt/alignmixup_cvpr22

공식 코드

AlignMixup: Improving Representations By Interpolating Aligned Features

https://github.com/shashiongithub/XSum

공식 코드

Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

https://github.com/shashiongithub/sidenet

공식 코드

Neural Extractive Summarization with Side Information

https://github.com/shaunyuan22/cfinet

공식 코드

Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learning

https://github.com/shawLyu/Occ-SDF-Hybrid

공식 코드

Learning a Room with the Occ-SDF Hybrid: Signed Distance Function Mingled with Occupancy Aids Scene Representation

https://github.com/shawkui/Proactive_Defensive_Backdoor

공식 코드

Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor

https://github.com/sheepooo/pit-position-invariant-transform

공식 코드

PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation

https://github.com/sheffieldnlp/mlqe-pe

공식 코드

MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset

https://github.com/shen-aoyu/CREST

공식 코드

CREST: An Efficient Conjointly-trained Spike-driven Framework for Event-based Object Detection Exploiting Spatiotemporal Dynamics

https://github.com/shengcao-cao/cmt

공식 코드

Contrastive Mean Teacher for Domain Adaptive Object Detectors

https://github.com/shengcao-cao/hassod

공식 코드

HASSOD: Hierarchical Adaptive Self-Supervised Object Detection

https://github.com/shengliu66/icv

공식 코드

In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

https://github.com/shengyuhao/divotrack

공식 코드

DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes

https://github.com/shentianxiao/language-style-transfer

공식 코드

Style Transfer from Non-Parallel Text by Cross-Alignment

https://github.com/shentianxiao/text-autoencoders

공식 코드

Educating Text Autoencoders: Latent Representation Guidance via Denoising

https://github.com/shenyi0220/cp-cluster

공식 코드

Confidence Propagation Cluster: Unleash Full Potential of Object Detectors

https://github.com/shenyunhang/ape

공식 코드

Aligning and Prompting Everything All at Once for Universal Visual Perception

https://github.com/shenyunhang/huwsod

공식 코드

HUWSOD: Holistic Self-training for Unified Weakly Supervised Object Detection

https://github.com/shenzheng2000/tpsence

공식 코드

TPSeNCE: Towards Artifact-Free Realistic Rain Generation for Deraining and Object Detection in Rain

https://github.com/shi-labs/natten

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Neighborhood Attention Transformer

https://github.com/shibu4064/indonlp

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From Scarcity to Capability: Empowering Fake News Detection in Low-Resource Languages with LLMs

https://github.com/shichaoy/cube_slam

공식 코드

CubeSLAM: Monocular 3D Object SLAM

https://github.com/shihe98/hcb

공식 코드

Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense

https://github.com/shihuahuang95/deim

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DEIM: DETR with Improved Matching for Fast Convergence

https://github.com/shijieS/SST

공식 코드

Deep Affinity Network for Multiple Object Tracking

https://github.com/shijing001/ffn_corpus

공식 코드

FFN: a Fine-grained Chinese-English Financial Domain Parallel Corpus

https://github.com/shikras/d-cube

공식 코드

Described Object Detection: Liberating Object Detection with Flexible Expressions

https://github.com/shinke-li/pointcvar

공식 코드

Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification

https://github.com/shinya7y/UniverseNet

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USB: Universal-Scale Object Detection Benchmark

https://github.com/shipra25jain/ESSNet

공식 코드

Scaling Semantic Segmentation Beyond 1K Classes on a Single GPU

https://github.com/shiqiu0419/pnp-3d

공식 코드

PnP-3D: A Plug-and-Play for 3D Point Clouds

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