Papers with Code 아카이브

Object Detection

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전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

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

https://github.com/iyatomilab/rsgaia_hbbt

공식 코드

Practical X-ray Gastric Cancer Diagnostic Support Using Refined Stochastic Data Augmentation and Hard Boundary Box Training

https://github.com/jack-admiral/ACM-MM-FRDT

공식 코드

RGB-D Salient Object Detection: A Survey

https://github.com/jackieam/e-inmemo

공식 코드

E-InMeMo: Enhanced Prompting for Visual In-Context Learning

https://github.com/jackieam/inmemo

공식 코드

Instruct Me More! Random Prompting for Visual In-Context Learning

https://github.com/jacky121298/wlst

공식 코드

WLST: Weak Labels Guided Self-training for Weakly-supervised Domain Adaptation on 3D Object Detection

https://github.com/jacobgil/pytorch-grad-cam

공식 코드

KPCA-CAM: Visual Explainability of Deep Computer Vision Models using Kernel PCA

https://github.com/jacobhenningsson95/synmfg_code

공식 코드

Domain Randomization for Object Detection in Manufacturing Applications using Synthetic Data: A Comprehensive Study

https://github.com/jacobi93/alpha-iou

공식 코드

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

https://github.com/jacobyuan7/ocn-hoi-benchmark

공식 코드

Detecting Human-Object Interactions with Object-Guided Cross-Modal Calibrated Semantics

https://github.com/jacobyuan7/rlipv2

공식 코드

RLIPv2: Fast Scaling of Relational Language-Image Pre-training

https://github.com/jaehakim97/sr4ir

공식 코드

Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss

https://github.com/jaeill/CVPR23-VNE

공식 코드

VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution

https://github.com/jalalilabucla/phycv

공식 코드

VEViD: Vision Enhancement via Virtual diffraction and coherent Detection

https://github.com/james128333/HarDNet-MSEG

공식 코드

HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS

https://github.com/janghyuncho/ecm-loss

공식 코드

Long-tail Detection with Effective Class-Margins

https://github.com/janmarcelkezmann/metadetect3d

공식 코드

LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds

https://github.com/jannctu/FINED

공식 코드

FINED: Fast Inference Network for Edge Detection

https://github.com/jaraxxus-me/airdet

공식 코드

AirDet: Few-Shot Detection without Fine-tuning for Autonomous Exploration

https://github.com/jarintotiondin/ziragroundingdino

공식 코드

Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection

https://github.com/jaryp/adaptivesemantictokencommunication

공식 코드

Adaptive Semantic Token Communication for Transformer-based Edge Inference

https://github.com/jason-lim26/dipex

공식 코드

DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection

https://github.com/jaychempan/ETS

공식 코드

Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detection

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