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코드

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

https://github.com/jerrysunning/drrnet

공식 코드

DRRNet: Macro-Micro Feature Fusion and Dual Reverse Refinement for Camouflaged Object Detection

https://github.com/jessiew0806/bi-lrfusion

공식 코드

Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection

https://github.com/jgiroux8/T_FFTRadNet

공식 코드

T-FFTRadNet: Object Detection with Swin Vision Transformers from Raw ADC Radar Signals

https://github.com/jgocm/ssl-detector

공식 코드

An Embedded Monocular Vision Approach for Ground-Aware Objects Detection and Position Estimation

https://github.com/jgwak/GSDN

공식 코드

Generative Sparse Detection Networks for 3D Single-shot Object Detection

https://github.com/jh-research/multipleteachers

공식 코드

Power of Cooperative Supervision: Multiple Teachers Framework for Enhanced 3D Semi-Supervised Object Detection

https://github.com/jhcho99/coformer

공식 코드

Collaborative Transformers for Grounded Situation Recognition

https://github.com/jhcho99/gsrtr

공식 코드

Grounded Situation Recognition with Transformers

https://github.com/jhl-det/rgbd_video_sod

공식 코드

ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection

https://github.com/jhl-hust/trasw

공식 코드

Tracklet-Switch Adversarial Attack against Pedestrian Multi-Object Tracking Trackers

https://github.com/jhuang81/weak-sup-visual-grounding

공식 코드

Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation

https://github.com/jiadingcn/geminifusion

공식 코드

GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer

https://github.com/jiahong-fu/kxnet

공식 코드

KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution

https://github.com/jiajiali04/semiweeds

공식 코드

Performance Evaluation of Semi-supervised Learning Frameworks for Multi-Class Weed Detection

https://github.com/jialeli1/from-voxel-to-point

공식 코드

From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decoder

https://github.com/jialeli1/mgaf-3dssd

공식 코드

Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloud

https://github.com/jiamian-wang/iterative-soft-shrinkage-sr

공식 코드

Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution

https://github.com/jiaming-wang/GLSD

공식 코드

GLSD: The Global Large-Scale Ship Database and Baseline Evaluations

https://github.com/jianghaojun/CondenseNetV2

공식 코드

CondenseNet V2: Sparse Feature Reactivation for Deep Networks

https://github.com/jiangsutx/SPMC_VideoSR

공식 코드

Detail-revealing Deep Video Super-resolution

https://github.com/jiangsutx/SRN-Deblur

공식 코드

Scale-recurrent Network for Deep Image Deblurring

https://github.com/jiangzhengkai/LSTS

공식 코드

Learning Where to Focus for Efficient Video Object Detection

https://github.com/jianzeli-114/dfosd

공식 코드

Distillation-Free One-Step Diffusion for Real-World Image Super-Resolution

https://github.com/jianzeli-114/fluxsr

공식 코드

One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation

https://github.com/jiaojiayuasd/dilateformer

공식 코드

DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition

https://github.com/jiaweihe1996/ba-det

공식 코드

3D Video Object Detection with Learnable Object-Centric Global Optimization

https://github.com/jiaweilian/benchmarking_physical_attack

공식 코드

PADetBench: Towards Benchmarking Physical Attacks against Object Detection

https://github.com/jiaweilian/padetbench

공식 코드

PADetBench: Towards Benchmarking Physical Attacks against Object Detection

https://github.com/jiaxi-wu/MPSR

공식 코드

Multi-Scale Positive Sample Refinement for Few-Shot Object Detection

https://github.com/jiayouqin/h-splitter

공식 코드

Motor Focus: Fast Ego-Motion Prediction for Assistive Visual Navigation

https://github.com/jiayuanwang-jw/yolov8-multi-task

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You Only Look at Once for Real-time and Generic Multi-Task

https://github.com/jiayuzou2020/diffbev

공식 코드

DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception

https://github.com/jichengyuan/cooperitive_students

공식 코드

Cooperative Students: Navigating Unsupervised Domain Adaptation in Nighttime Object Detection

https://github.com/jimas95/CMinMax

공식 코드

cMinMax: A Fast Algorithm to Find the Corners of an N-dimensional Convex Polytope

https://github.com/jimmyma99/sarchat

공식 코드

SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR Image Interpretation

https://github.com/jin-s13/unifs

공식 코드

UniFS: Universal Few-shot Instance Perception with Point Representations

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