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2D Classification

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

https://github.com/ut-amrl/coda-models

공식 코드

Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset

https://github.com/ut-vision/FgSty-CPL

공식 코드

Foreground-Aware Stylization and Consensus Pseudo-Labeling for Domain Adaptation of First-Person Hand Segmentation

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

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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

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

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

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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

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Recurrent Vision Transformers for Object Detection with Event Cameras

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

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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/v0lta/wavelet-network-compression

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Neural network compression via learnable wavelet transforms

https://github.com/vabatista/slr_transformers_ehr

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Application of Transformers based methods in Electronic Medical Records: A Systematic Literature Review

https://github.com/vacancy/PreciseRoIPooling

공식 코드

Acquisition of Localization Confidence for Accurate Object Detection

https://github.com/vagisha-nidhi/TextSummarizer

공식 코드

Extractive Summarization using Deep Learning

https://github.com/vaibhav-khamankar/fusestyle

공식 코드

Histopathological Image Analysis with Style-Augmented Feature Domain Mixing for Improved Generalization

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

공식 코드

A Closer Look at Smoothness in Domain Adversarial Training

https://github.com/valentinkoch/svdna

공식 코드

Noise transfer for unsupervised domain adaptation of retinal OCT images

https://github.com/valeoai/MVRSS

공식 코드

Multi-View Radar Semantic Segmentation

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

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

https://github.com/valeoai/also

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ALSO: Automotive Lidar Self-supervision by Occupancy estimation

https://github.com/valeoai/obow

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

https://github.com/valeoai/slidr

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

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

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

https://github.com/vastlik/symformer

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SymFormer: End-to-end symbolic regression using transformer-based architecture

https://github.com/vdeborto/cdsb

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Conditional Simulation Using Diffusion Schrödinger Bridges

https://github.com/vdenberg/context-in-informational-bias-detection

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Context in Informational Bias Detection

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

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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

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