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Object Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ekut-es/mr3d-net
공식 코드MR3D-Net: Dynamic Multi-Resolution 3D Sparse Voxel Grid Fusion for LiDAR-Based Collective Perception
https://github.com/elischwartz/maeday
공식 코드https://github.com/elvintanhust/monocd
공식 코드MonoCD: Monocular 3D Object Detection with Complementary Depths
https://github.com/emanuelevivoli/CoMix
공식 코드CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding
https://github.com/emanuelevivoli/awesome-comics-understanding
공식 코드One missing piece in Vision and Language: A Survey on Comics Understanding
https://github.com/emanuelevivoli/cdf
공식 코드Comics Datasets Framework: Mix of Comics datasets for detection benchmarking
https://github.com/embeddedml-edagroup/pit
공식 코드Lightweight Neural Architecture Search for Temporal Convolutional Networks at the Edge
https://github.com/emecercelik/Temp-Frustum-Net
공식 코드https://github.com/emecercelik/ssl-3d-detection
공식 코드3D Object Detection with a Self-supervised Lidar Scene Flow Backbone
https://github.com/emirhanbayar/fast-deep-oc-sort
공식 코드When to Extract ReID Features: A Selective Approach for Improved Multiple Object Tracking
https://github.com/emirhanbayar/fast-strongsort
공식 코드When to Extract ReID Features: A Selective Approach for Improved Multiple Object Tracking
https://github.com/encounter1997/SFA
공식 코드Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers
https://github.com/endernewton/tf-faster-rcnn
공식 코드An Implementation of Faster RCNN with Study for Region Sampling
https://github.com/enesdoruk/damamba
공식 코드DA-Mamba: Domain Adaptive Hybrid Mamba-Transformer Based One-Stage Object Detection
https://github.com/enesdoruk/davimnet
공식 코드DA-Mamba: Domain Adaptive Hybrid Mamba-Transformer Based One-Stage Object Detection
https://github.com/engzenia/wIoU
공식 코드Weighted Intersection over Union (wIoU) for Evaluating Image Segmentation
https://github.com/envision-research/generalizable-bev
공식 코드Towards Generalizable Multi-Camera 3D Object Detection via Perspective Debiasing
https://github.com/envision-research/scale-bev
공식 코드Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting
https://github.com/epfl-imos/simple-sfod
공식 코드https://github.com/er-muyue/defrcn
공식 코드DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
https://github.com/erbloo/raan
공식 코드https://github.com/erbloo/wAP_feature_squeezing
공식 코드https://github.com/ergowho/firefly2.0
공식 코드https://github.com/ericdengbowen/dslrdnet
공식 코드Addressing Multiple Salient Object Detection via Dual-Space Long-Range Dependencies
https://github.com/ericyi/GSPN
공식 코드GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud
https://github.com/erikvalle/consensus-focus-for-object-detection
공식 코드https://github.com/erkara/trackingdroplets
공식 코드Deep Learning Based Object Tracking in Walking Droplet and Granular Intruder Experiments
https://github.com/ermongroup/NDA
공식 코드https://github.com/eslambakr/emca
공식 코드https://github.com/essunny310/freestylenet
공식 코드https://github.com/estrellaxyu/differential-alignment-for-daod
공식 코드https://github.com/eternaldolphin/lami-detr
공식 코드LaMI-DETR: Open-Vocabulary Detection with Language Model Instruction
https://github.com/eth-disco/cue-detr
공식 코드https://github.com/eth-pbl/cr3dt
공식 코드https://github.com/event-ahu/openevdet
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.