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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/yichen928/sparsefusion

공식 코드

SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection

https://github.com/yiduohao/radical

공식 코드

Bootstrapping Autonomous Driving Radars with Self-Supervised Learning

https://github.com/yifanlu0227/coalign

공식 코드

Robust Collaborative 3D Object Detection in Presence of Pose Errors

https://github.com/yifanxu74/mq-det

공식 코드

Multi-modal Queried Object Detection in the Wild

https://github.com/yifanzhang713/ia-ssd

공식 코드

Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds

https://github.com/yihongXU/TransCenter

공식 코드

TransCenter: Transformers with Dense Representations for Multiple-Object Tracking

https://github.com/yihongsun/mod-uv

공식 코드

MOD-UV: Learning Mobile Object Detectors from Unlabeled Videos

https://github.com/yihui-he/KL-Loss

공식 코드

Bounding Box Regression with Uncertainty for Accurate Object Detection

https://github.com/yihui-he/epipolar-transformers

공식 코드

Epipolar Transformers

https://github.com/yihui-he/softer-NMS

공식 코드

Bounding Box Regression with Uncertainty for Accurate Object Detection

https://github.com/yijia-xiao/protein-llm-survey

공식 코드

Protein Large Language Models: A Comprehensive Survey

https://github.com/yijingru/ASSD-Pytorch

공식 코드

ASSD: Attentive Single Shot Multibox Detector

https://github.com/yijingru/BBAVectors-Oriented-Object-Detection

공식 코드

Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

https://github.com/yijingru/KG_Instance_Segmentation

공식 코드

Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes

https://github.com/yijingru/ObjGuided-Instance-Segmentation

공식 코드

Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images

https://github.com/yikaiw/TokenFusion

공식 코드

Multimodal Token Fusion for Vision Transformers

https://github.com/yikang-li/MSDN

공식 코드

Scene Graph Generation from Objects, Phrases and Region Captions

https://github.com/yilihsu/asktoknowmore

공식 코드

Ask to Know More: Generating Counterfactual Explanations for Fake Claims

https://github.com/yilonglv/aid

공식 코드

Anchor-Intermediate Detector: Decoupling and Coupling Bounding Boxes for Accurate Object Detection

https://github.com/yimeng-fan/SFOD

공식 코드

SFOD: Spiking Fusion Object Detector

https://github.com/yimeng-fan/spikssd

공식 코드

SpikSSD: Better Extraction and Fusion for Object Detection with Spiking Neuron Networks

https://github.com/yinghuagao/siba

공식 코드

Backdoor Attack with Sparse and Invisible Trigger

https://github.com/yingtaomj/VMSMO

공식 코드

VMSMO: Learning to Generate Multimodal Summary for Video-based News Articles

https://github.com/yingutk/NL-MAT

공식 코드

Non-Local Representation based Mutual Affine-Transfer Network for Photorealistic Stylization

https://github.com/yinjunbo/3DVID

공식 코드

LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention

https://github.com/yinjunbo/is-fusion

공식 코드

IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection

https://github.com/yinjunbo/proficientteachers

공식 코드

Semi-supervised 3D Object Detection with Proficient Teachers

https://github.com/yinjunbo/proposalcontrast

공식 코드

ProposalContrast: Unsupervised Pre-training for LiDAR-based 3D Object Detection

https://github.com/yinjunbo/ssda3d

공식 코드

SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud

https://github.com/yinmh17/DNL-Semantic-Segmentation

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Disentangled Non-Local Neural Networks

https://github.com/yinwenpeng/BenchmarkingZeroShot

공식 코드

Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach

https://github.com/yinyf0804/wsod-cbl

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Cyclic-Bootstrap Labeling for Weakly Supervised Object Detection

https://github.com/yinyjin/dualanodiff

공식 코드

DualAnoDiff: Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation

https://github.com/yinyunie/RfDNet

공식 코드

RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction

https://github.com/yinyunie/Total3DUnderstanding

공식 코드

Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image

https://github.com/yinzhu-quan/lm-evaluation-harness

공식 코드

EconLogicQA: A Question-Answering Benchmark for Evaluating Large Language Models in Economic Sequential Reasoning

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