https://github.com/vision-agh/mmar_2023
공식 코드Detection-segmentation convolutional neural network for autonomous vehicle perception
Papers with Code 아카이브
2D Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/vision-agh/mt_kria
공식 코드https://github.com/vision-agh/pointpillars-backbone
공식 코드PointPillars Backbone Type Selection For Fast and Accurate LiDAR Object Detection
https://github.com/vision-sjtu/quadmamba
공식 코드QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model
https://github.com/visionlearninggroup/mind_back
공식 코드Mind the Backbone: Minimizing Backbone Distortion for Robust Object Detection
https://github.com/visionlearninggroup/uda_poseestimation
공식 코드https://github.com/visionverse/blind-motion-deblurring-survey
공식 코드Deep learning in motion deblurring: current status, benchmarks and future prospects
https://github.com/visionxlab/point2rbox-v2
공식 코드https://github.com/visionxlab/whollywood
공식 코드https://github.com/visionxlab/whollywood-jittor
공식 코드https://github.com/visresearch/MultipleObjectStitching
공식 코드Multiple Object Stitching for Unsupervised Representation Learning
https://github.com/visresearch/aps
공식 코드https://github.com/visresearch/mgc
공식 코드Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning
https://github.com/visresearch/patchmix
공식 코드https://github.com/vistec-AI/thai2transformers
공식 코드WangchanBERTa: Pretraining transformer-based Thai Language Models
https://github.com/visual-conception-group/localized-perception-constrained-vision-systems
공식 코드https://github.com/visual-words/visual-words
공식 코드https://github.com/visualaikhu/monowad
공식 코드MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object Detection
https://github.com/viswas1/TinyML
공식 코드Real Time Object Detection System with YOLO and CNN Models: A Review
https://github.com/visym/keynet
공식 코드Key-Nets: Optical Transformation Convolutional Networks for Privacy Preserving Vision Sensors
https://github.com/vita-epfl/butterflydetector
공식 코드https://github.com/vita-epfl/monoloco
공식 코드MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation
https://github.com/vita-epfl/motion-style-transfer
공식 코드Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting
https://github.com/vita-group/font_completion_graph
공식 코드Font Completion and Manipulation by Cycling Between Multi-Modality Representations
https://github.com/vita-group/slak
공식 코드More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity
https://github.com/vitae-transformer/bevsimdet
공식 코드SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection
https://github.com/vitae-transformer/mtp
공식 코드MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
https://github.com/vitae-transformer/qformer
공식 코드https://github.com/vitae-transformer/remote-sensing-rvsa
공식 코드Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model
https://github.com/vitae-transformer/rsp
공식 코드https://github.com/vitae-transformer/samrs
공식 코드SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model
https://github.com/vitae-transformer/simdistill
공식 코드SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection
https://github.com/vitae-transformer/vitae-transformer-remote-sensing
공식 코드https://github.com/vitae-transformer/vitae-vsa
공식 코드VSA: Learning Varied-Size Window Attention in Vision Transformers
https://github.com/vitjanz/draem
공식 코드DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detection
https://github.com/vivek3141/ghostbuster
공식 코드Ghostbuster: Detecting Text Ghostwritten by Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.