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평가표

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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/air-thu/dair-rcooper

공식 코드

RCooper: A Real-world Large-scale Dataset for Roadside Cooperative Perception

https://github.com/air-thu/dair-v2x

공식 코드

DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection

https://github.com/airl-iisc/indraeye

공식 코드

SAGA: Semantic-Aware Gray color Augmentation for Visible-to-Thermal Domain Adaptation across Multi-View Drone and Ground-Based Vision Systems

https://github.com/airotau/pointpillarshailoinnoviz

공식 코드

Real-Time 3D Object Detection Using InnovizOne LiDAR and Low-Power Hailo-8 AI Accelerator

https://github.com/airou-lab/SynthCRAV

공식 코드

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets

https://github.com/ais-bonn/jetsontrtperception

공식 코드

3D Semantic Scene Perception using Distributed Smart Edge Sensors

https://github.com/ais-bonn/smartedgesensor3dsceneperception

공식 코드

3D Semantic Scene Perception using Distributed Smart Edge Sensors

https://github.com/ais-clemson/visiongpt

공식 코드

VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation

https://github.com/aitical/cfsr

공식 코드

Transforming Image Super-Resolution: A ConvFormer-based Efficient Approach

https://github.com/aitical/scnet

공식 코드

Fully $1\times1$ Convolutional Network for Lightweight Image Super-Resolution

https://github.com/aitical/sscsr

공식 코드

Exploiting Self-Supervised Constraints in Image Super-Resolution

https://github.com/aitical/tcsr

공식 코드

Incorporating Transformer Designs into Convolutions for Lightweight Image Super-Resolution

https://github.com/aitor-martinez-seras/ood_in_object_detection

공식 코드

On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution Data

https://github.com/aitor-martinez-seras/snn-automotive-object-detection

공식 코드

Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object Discovery

https://github.com/aixmobility/the-drift

공식 코드

DRIFT open dataset: A drone-derived intelligence for traffic analysis in urban environmen

https://github.com/ajaychawda58/id_cnn

공식 코드

Dimensionality of datasets in object detection networks

https://github.com/ajedgley/rebound

공식 코드

ReBound: An Open-Source 3D Bounding Box Annotation Tool for Active Learning

https://github.com/ajhamdi/SADA

공식 코드

SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications

https://github.com/ajiljalal/code-cs-fairness

공식 코드

Fairness for Image Generation with Uncertain Sensitive Attributes

https://github.com/akasha-imaging/iccv2021

공식 코드

Towards Rotation Invariance in Object Detection

https://github.com/akhilpm/dronedetectron2

공식 코드

Cascaded Zoom-in Detector for High Resolution Aerial Images

https://github.com/akhilpm/dronessod

공식 코드

Density Crop-guided Semi-supervised Object Detection in Aerial Images

https://github.com/akhilpm/semiwsod

공식 코드

Semi-Weakly Supervised Object Detection by Sampling Pseudo Ground-Truth Boxes

https://github.com/akhtarvision/bpc_calibration

공식 코드

Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection

https://github.com/akirahero/diffindscene

공식 코드

DiffInDScene: Diffusion-based High-Quality 3D Indoor Scene Generation

https://github.com/aklein1995/drise_dmfpp_ddeletion

공식 코드

On the Black-box Explainability of Object Detection Models for Safe and Trustworthy Industrial Applications

https://github.com/akola-mbey-denis/efficientensemble

공식 코드

How To Effectively Train An Ensemble Of Faster R-CNN Object Detectors To Quantify Uncertainty

https://github.com/akshaydudhane16/bipnet

공식 코드

Burst Image Restoration and Enhancement

https://github.com/akshitac8/ow-detr

공식 코드

OW-DETR: Open-world Detection Transformer

https://github.com/aktgpt/vq-nnf

공식 코드

Efficient High-Resolution Template Matching with Vector Quantized Nearest Neighbour Fields

https://github.com/akuxcw/GridMask

공식 코드

GridMask Data Augmentation

https://github.com/alanli1997/rethinking-fpn

공식 코드

Rethinking Features-Fused-Pyramid-Neck for Object Detection

https://github.com/alanli1997/slim-neck-by-gsconv

공식 코드

Slim-neck by GSConv: A lightweight-design for real-time detector architectures

https://github.com/albert-jin/cvt-assd

공식 코드

CvT-ASSD: Convolutional vision-Transformer Based Attentive Single Shot MultiBox Detector

https://github.com/alea-institute/kl3m-tokenizer-paper

공식 코드

KL3M Tokenizers: A Family of Domain-Specific and Character-Level Tokenizers for Legal, Financial, and Preprocessing Applications

https://github.com/alexacarlson/SensorEffectAugmentation

공식 코드

Modeling Camera Effects to Improve Visual Learning from Synthetic Data

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