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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/utaustin-swarmlab/task-aware-distributed-source-coding

공식 코드

Task-aware Distributed Source Coding under Dynamic Bandwidth

https://github.com/utokyo-fieldphenomics-lab/doda

공식 코드

DODA: Diffusion for Object-detection Domain Adaptation in Agriculture

https://github.com/uulm-mrm/mmood3d

공식 코드

Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection

https://github.com/uw-cmg/cavity_defect_detection

공식 코드

Predicting Performance of Object Detection Models in Electron Microscopy Using Random Forests

https://github.com/uw-cmg/defectstemvideoanalysis

공식 코드

A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations

https://github.com/uzh-rpg/event_representation_study

공식 코드

From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection

https://github.com/uzh-rpg/rpg_asynet

공식 코드

Event-based Asynchronous Sparse Convolutional Networks

https://github.com/uzh-rpg/rpg_ev-transfer

공식 코드

Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation

https://github.com/uzh-rpg/rpg_ramnet

공식 코드

Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction

https://github.com/uzh-rpg/rvt

공식 코드

Recurrent Vision Transformers for Object Detection with Event Cameras

https://github.com/uzh-rpg/ssms_event_cameras

공식 코드

State Space Models for Event Cameras

https://github.com/uzh-rpg/svit

공식 코드

Revisiting Token Pruning for Object Detection and Instance Segmentation

https://github.com/uzkent/EfficientObjectDetection

공식 코드

Efficient Object Detection in Large Images using Deep Reinforcement Learning

https://github.com/v-andrearczyk/caffe-TCNN

공식 코드

Using Filter Banks in Convolutional Neural Networks for Texture Classification

https://github.com/vacancy/PreciseRoIPooling

공식 코드

Acquisition of Localization Confidence for Accurate Object Detection

https://github.com/val-iisc/sdat

공식 코드

A Closer Look at Smoothness in Domain Adversarial Training

https://github.com/valeoai/MVRSS

공식 코드

Multi-View Radar Semantic Segmentation

https://github.com/valeoai/SemanticPalette

공식 코드

Semantic Palette: Guiding Scene Generation with Class Proportions

https://github.com/valeoai/WoodScape/tree/master/omnidet

공식 코드

OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving

https://github.com/valeoai/also

공식 코드

ALSO: Automotive Lidar Self-supervision by Occupancy estimation

https://github.com/valeoai/obow

공식 코드

OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning

https://github.com/valeoai/slidr

공식 코드

Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data

https://github.com/valfride/lpr-rsr

공식 코드

Combining Attention Module and Pixel Shuffle for License Plate Super-Resolution

https://github.com/valfride/lpr-rsr-ext

공식 코드

Super-Resolution of License Plate Images Using Attention Modules and Sub-Pixel Convolution Layers

https://github.com/valiantdiligent/uav-detr

공식 코드

UAV-DETR: Efficient End-to-End Object Detection for Unmanned Aerial Vehicle Imagery

https://github.com/vdeborto/cdsb

공식 코드

Conditional Simulation Using Diffusion Schrödinger Bridges

https://github.com/vdigpku/bev-mae

공식 코드

BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios

https://github.com/vdigpku/formula

공식 코드

Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised Object Discovery with Transformers

https://github.com/vdigpku/henet

공식 코드

HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras

https://github.com/vdigpku/nas-bnn

공식 코드

NAS-BNN: Neural Architecture Search for Binary Neural Networks

https://github.com/vdigpku/rcbevdet

공식 코드

RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detection

https://github.com/vdigpku/t-sea

공식 코드

T-SEA: Transfer-based Self-Ensemble Attack on Object Detection

https://github.com/vdigpku/teocc

공식 코드

TEOcc: Radar-camera Multi-modal Occupancy Prediction via Temporal Enhancement

https://github.com/vdorbala/LGX

공식 코드

Can an Embodied Agent Find Your "Cat-shaped Mug"? LLM-Guided Exploration for Zero-Shot Object Navigation

https://github.com/velatkilic/LISA

공식 코드

Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object Detection

https://github.com/velodc/oshot_detection

공식 코드

Exploring Data Aggregation and Transformations to Generalize across Visual Domains

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