Papers with Code 아카이브

2D Object Detection

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하위 태스크

15

평가표

20

보존된 평가 기록

57

코드

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

https://github.com/implus/GFocal

공식 코드

Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

https://github.com/implus/GFocalV2

공식 코드

Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection

https://github.com/implus/PytorchInsight

공식 코드

Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks

https://github.com/implus/RecursiveMix-pytorch

공식 코드

RecursiveMix: Mixed Learning with History

https://github.com/implus/um-mae

공식 코드

Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality

https://github.com/imrl/umad

공식 코드

UMAD: University of Macau Anomaly Detection Benchmark Dataset

https://github.com/imruljubair/BdSLImset

공식 코드

Real Time Bangladeshi Sign Language Detection using Faster R-CNN

https://github.com/inakierregueab/yolo11-jde

공식 코드

YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID

https://github.com/inconstance/t-shirt-natural-backdoor-dataset

공식 코드

TransCAB: Transferable Clean-Annotation Backdoor to Object Detection with Natural Trigger in Real-World

https://github.com/industryessentials/ymir

공식 코드

ALBench: A Framework for Evaluating Active Learning in Object Detection

https://github.com/inexascale/pychop

공식 코드

Pychop: Emulating Low-Precision Arithmetic in Numerical Methods and Neural Networks

https://github.com/infinity7428/hANMCL

공식 코드

Hierarchical Attention Network for Few-Shot Object Detection via Meta-Contrastive Learning

https://github.com/insdet/instance-detection

공식 코드

A High-Resolution Dataset for Instance Detection with Multi-View Instance Capture

https://github.com/inspire-group/ObjectSeeker

공식 코드

ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking

https://github.com/inspire-group/detectorguard

공식 코드

DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks

https://github.com/intcomp/camouflaged-vlm

공식 코드

Open-Vocabulary Camouflaged Object Segmentation with Cascaded Vision Language Models

https://github.com/intelligent-exploration/IP_MinEx

공식 코드

Computer vision-based framework for extracting geological lineaments from optical remote sensing data

https://github.com/inverted-ai/object-detection

공식 코드

Realistically distributing object placements in synthetic training data improves the performance of vision-based object detection models

https://github.com/ioangatop/srVAE

공식 코드

Self-Supervised Variational Auto-Encoders

https://github.com/iqtlabs/camolo

공식 코드

The Weaknesses of Adversarial Camouflage in Overhead Imagery

https://github.com/iranqin/supfusion

공식 코드

SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection

https://github.com/ireneperezsalesa/event_tracking

공식 코드

Event-based Visual Tracking in Dynamic Environments

https://github.com/irfanICMLL/structure_knowledge_distillation

공식 코드

Structured Knowledge Distillation for Dense Prediction

https://github.com/irikos/rip_currents

공식 코드

Rip Current Segmentation: A Novel Benchmark and YOLOv8 Baseline Results

https://github.com/isbrycee/gem

공식 코드

GEM: Boost Simple Network for Glass Surface Segmentation via Vision Foundation Models

https://github.com/isee-laboratory/bpf

공식 코드

Bridge Past and Future: Overcoming Information Asymmetry in Incremental Object Detection

https://github.com/isee-laboratory/hd-ovd

공식 코드

A Hierarchical Semantic Distillation Framework for Open-Vocabulary Object Detection

https://github.com/iseri27/tg_gbc

공식 코드

Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning

https://github.com/isl-cv/udi

공식 코드

Unsqueeze [CLS] Bottleneck to Learn Rich Representations

https://github.com/itsshuvra/A-Deep-Learning-Framework-to-Reconstruct-Face-under-Mask

공식 코드

A Deep Learning Framework to Reconstruct Face under Mask

https://github.com/ivMCL/AttentiveNorm_Detection

공식 코드

Attentive Normalization

https://github.com/ivadomed/ivadomed

공식 코드

ivadomed: A Medical Imaging Deep Learning Toolbox

https://github.com/ivmcl/pacavit

공식 코드

PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers

https://github.com/ixiaohuihuihui/gcc-net

공식 코드

A Gated Cross-domain Collaborative Network for Underwater Object Detection

https://github.com/ixilai/mfif-mmif

공식 코드

Bridging the Gap between Multi-focus and Multi-modal: A Focused Integration Framework for Multi-modal Image Fusion

https://github.com/ixilai/samf

공식 코드

SAMF: Small-Area-Aware Multi-focus Image Fusion for Object Detection

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