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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/kai-liu001/condiquant

공식 코드

CondiQuant: Condition Number Based Low-Bit Quantization for Image Super-Resolution

https://github.com/kai3316/yolic-labeling

공식 코드

YOLIC: An Efficient Method for Object Localization and Classification on Edge Devices

https://github.com/kailigo/cddod

공식 코드

Cross-Domain Document Object Detection: Benchmark Suite and Method

https://github.com/kaist-avelab/k-radar

공식 코드

K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions

https://github.com/kaixinbear/CAPE

공식 코드

CAPE: Camera View Position Embedding for Multi-View 3D Object Detection

https://github.com/kakaobrain/HOTR

공식 코드

HOTR: End-to-End Human-Object Interaction Detection with Transformers

https://github.com/kakaobrain/solvent

공식 코드

Solvent: A Framework for Protein Folding

https://github.com/kakaobrain/sparse-detr

공식 코드

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

https://github.com/kancharlavamshi/icip2023_challenge

공식 코드

Overcoming Scene Context Constraints for Object Detection in wild using Defilters

https://github.com/kangliao929/cylin-painting

공식 코드

Cylin-Painting: Seamless {360\textdegree} Panoramic Image Outpainting and Beyond

https://github.com/karoslyx/mffssr

공식 코드

Multi-Level Feature Fusion Network for Lightweight Stereo Image Super-Resolution

https://github.com/karthickpgunasekaran/superresolutionwithrdn

공식 코드

Ultra Sharp : Study of Single Image Super Resolution using Residual Dense Network

https://github.com/karttikeya/minrev

공식 코드

Reversible Vision Transformers

https://github.com/kau-quantumailab/rfpar

공식 코드

Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object Detection

https://github.com/kbui1993/NonconvexNetworkSlimming

공식 코드

Improving Network Slimming with Nonconvex Regularization

https://github.com/kcl-bmeis/ultraflwr

공식 코드

UltraFlwr -- An Efficient Federated Medical and Surgical Object Detection Framework

https://github.com/kcyu2014/lidar-camera-robust-benchmark

공식 코드

Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection

https://github.com/kdexd/coco-rem

공식 코드

Benchmarking Object Detectors with COCO: A New Path Forward

https://github.com/kdexd/virtex

공식 코드

VirTex: Learning Visual Representations from Textual Annotations

https://github.com/keenyjin/soia-dod

공식 코드

Short-term Object Interaction Anticipation with Disentangled Object Detection @ Ego4D Short Term Object Interaction Anticipation Challenge

https://github.com/kemaloksuz/BoundingBoxGenerator

공식 코드

Generating Positive Bounding Boxes for Balanced Training of Object Detectors

https://github.com/kemaloksuz/LRP-Error

공식 코드

One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks

https://github.com/kemaloksuz/ObjectDetectionImbalance

공식 코드

Imbalance Problems in Object Detection: A Review

https://github.com/kemaloksuz/RankSortLoss

공식 코드

Rank & Sort Loss for Object Detection and Instance Segmentation

https://github.com/kemaloksuz/aLRPLoss

공식 코드

A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection

https://github.com/kemo-huang/jmodt

공식 코드

Joint Multi-Object Detection and Tracking with Camera-LiDAR Fusion for Autonomous Driving

https://github.com/kentaroy47/DatasetCulling

공식 코드

Dataset Culling: Towards Efficient Training Of Distillation-Based Domain Specific Models

https://github.com/kentaroy47/training-domain-specific-models

공식 코드

Training Domain Specific Models for Energy-Efficient Object Detection

https://github.com/kerenfu/JLDCF

공식 코드

JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection

https://github.com/kerenfu/LFSOD-Survey

공식 코드

Light Field Salient Object Detection: A Review and Benchmark

https://github.com/kerenfu/rdvs

공식 코드

Salient Object Detection in RGB-D Videos

https://github.com/kevalmorabia97/Object-and-Semantic-Part-Detection-pyTorch

공식 코드

Attention-based Joint Detection of Object and Semantic Part

https://github.com/kevalmorabia97/cova-web-object-detection

공식 코드

CoVA: Context-aware Visual Attention for Webpage Information Extraction

https://github.com/kevin-klein/autarch-material

공식 코드

AutArch: An AI-assisted workflow for object detection and automated recording in archaeological catalogues

https://github.com/kevin-ssy/ViP

공식 코드

Visual Parser: Representing Part-whole Hierarchies with Transformers

https://github.com/kevinhkhsu/DA_detection

공식 코드

Progressive Domain Adaptation for Object Detection

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