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보존된 평가 기록

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코드

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

https://github.com/wangchen1801/fpd

공식 코드

Fine-Grained Prototypes Distillation for Few-Shot Object Detection

https://github.com/wangck20/globalmamba

공식 코드

GlobalMamba: Global Image Serialization for Vision Mamba

https://github.com/wangck20/opera

공식 코드

OPERA: Omni-Supervised Representation Learning with Hierarchical Supervisions

https://github.com/wangck20/v2m

공식 코드

V2M: Visual 2-Dimensional Mamba for Image Representation Learning

https://github.com/wanggrun/Adaptively-Connected-Neural-Networks

공식 코드

Adaptively Connected Neural Networks

https://github.com/wangguanan/denoiserep

공식 코드

DenoiseRep: Denoising Model for Representation Learning

https://github.com/wangguojun2018/CenterNet3d

공식 코드

CenterNet3D: An Anchor Free Object Detector for Point Cloud

https://github.com/wangguojun2018/MVAF-Net

공식 코드

Multi-View Adaptive Fusion Network for 3D Object Detection

https://github.com/wanghao9610/ov-dino

공식 코드

OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion

https://github.com/wangle53/anodfdnet

공식 코드

AnoDFDNet: A Deep Feature Difference Network for Anomaly Detection

https://github.com/wangsch10/v2x-dgpe

공식 코드

V2X-DGPE: Addressing Domain Gaps and Pose Errors for Robust Collaborative 3D Object Detection

https://github.com/wangsr126/RDSNet

공식 코드

RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation

https://github.com/wangsr126/ndet

공식 코드

Narrowing the Gap: Improved Detector Training with Noisy Location Annotations

https://github.com/wangwen-whu/wtw-dataset

공식 코드

Parsing Table Structures in the Wild

https://github.com/wangxiyang2022/YONTD-MOT

공식 코드

You Only Need Two Detectors to Achieve Multi-Modal 3D Multi-Object Tracking

https://github.com/wangyongqi558/METOR

공식 코드

METOR: A Unified Framework for Mutual Enhancement of Objects and Relationships in Open-vocabulary Video Visual Relationship Detection

https://github.com/wangys16/ohda

공식 코드

Syn-to-Real Unsupervised Domain Adaptation for Indoor 3D Object Detection

https://github.com/wangyu-ustc/memoryllm

공식 코드

M+: Extending MemoryLLM with Scalable Long-Term Memory

https://github.com/wangyueft/detr3d

공식 코드

DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries

https://github.com/wangzcbruce/dhd

공식 코드

Drones Help Drones: A Collaborative Framework for Multi-Drone Object Trajectory Prediction and Beyond

https://github.com/wanzysky/SlenderObjDet

공식 코드

Slender Object Detection: Diagnoses and Improvements

https://github.com/warlockwendell/aggdet

공식 코드

Training-free Boost for Open-Vocabulary Object Detection with Confidence Aggregation

https://github.com/warriordby/lfx

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Unifying Light Field Perception with Field of Parallax

https://github.com/waterscenes/waterscenes

공식 코드

WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces

https://github.com/waveboo/clis

공식 코드

Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative Learning

https://github.com/waymo-research/waymo-open-dataset

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LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection

https://github.com/wb014/FreeGS

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Bootstraping Clustering of Gaussians for View-consistent 3D Scene Understanding

https://github.com/wchao0601/m4-sar

공식 코드

M4-SAR: A Multi-Resolution, Multi-Polarization, Multi-Scene, Multi-Source Dataset and Benchmark for Optical-SAR Fusion Object Detection

https://github.com/wcyjerry/UCFnet

공식 코드

Local Contrast and Global Contextual Information Make Infrared Small Object Salient Again

https://github.com/wcyjerry/basicisos

공식 코드

Local Contrast and Global Contextual Information Make Infrared Small Object Salient Again

https://github.com/wdhudiekou/irfs

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An Interactively Reinforced Paradigm for Joint Infrared-Visible Image Fusion and Saliency Object Detection

https://github.com/wdhudiekou/stsc

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Semantic-aware Texture-Structure Feature Collaboration for Underwater Image Enhancement

https://github.com/wdmwhh/MRefSR

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LMR: A Large-Scale Multi-Reference Dataset for Reference-based Super-Resolution

https://github.com/wds320/AAAI_Event_based_detection

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Dual Memory Aggregation Network for Event-Based Object Detection with Learnable Representation

https://github.com/we1pingyu/CALD

공식 코드

Consistency-based Active Learning for Object Detection

https://github.com/we1pingyu/DSHNet

공식 코드

Towards Resolving the Challenge of Long-tail Distribution in UAV Images for Object Detection

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