https://github.com/hzhupku/DCNet
공식 코드Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection
Papers with Code 아카이브
Object Detection
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hzx-9894/mma
공식 코드https://github.com/i-gao/adavision
공식 코드https://github.com/iVMCL/AOGNet-v2
공식 코드https://github.com/iVMCL/AOGNets
공식 코드AOGNets: Compositional Grammatical Architectures for Deep Learning
https://github.com/iai-hrc/ha-vid
공식 코드HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
https://github.com/iamaaditya/image-compression-cnn
공식 코드Semantic Perceptual Image Compression using Deep Convolution Networks
https://github.com/ibm-aur-nlp/PubLayNet
공식 코드https://github.com/ibm-aur-nlp/PubTabNet
공식 코드https://github.com/ibm/synthtabnet
공식 코드TableFormer: Table Structure Understanding with Transformers
https://github.com/ibrahimethemhamamci/hierarchicaldet
공식 코드Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays
https://github.com/icarofua/vehicle-rear
공식 코드https://github.com/icey-zhang/E2E-MFD
공식 코드E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection
https://github.com/icey-zhang/SuperYOLO
공식 코드SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing Imagery
https://github.com/icey-zhang/ghost
공식 코드https://github.com/icvteam/pgnet
공식 코드Pyramid Grafting Network for One-Stage High Resolution Saliency Detection
https://github.com/idea-research/dino-x-api
공식 코드DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding
https://github.com/idea-research/dn-detr
공식 코드DN-DETR: Accelerate DETR Training by Introducing Query DeNoising
https://github.com/idea-research/dq-detr
공식 코드DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding
https://github.com/idea-research/grounding-dino-1.5-api
공식 코드Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
https://github.com/idea-research/groundingdino
공식 코드Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
https://github.com/idea-research/lite-detr
공식 코드Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETR
https://github.com/idea-research/maskdino
공식 코드Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation
https://github.com/idea-research/rexseek
공식 코드https://github.com/idea-research/t-rex
공식 코드T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy
https://github.com/idejie/KAD
공식 코드Active Object Detection with Knowledge Aggregation and Distillation from Large Models
https://github.com/idiosyncracies/Sebica
공식 코드Sebica: Lightweight Spatial and Efficient Bidirectional Channel Attention Super Resolution Network
https://github.com/idrl-lab/Full-coverage-camouflage-adversarial-attack
공식 코드FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack
https://github.com/idstcv/DR_loss
공식 코드DR Loss: Improving Object Detection by Distributional Ranking
https://github.com/iduta/coconv
공식 코드https://github.com/iduta/iresnet
공식 코드https://github.com/iduta/pyconv
공식 코드Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
https://github.com/ies-research/uncertainty-object-detection
공식 코드A Review of Uncertainty Calibration in Pretrained Object Detectors
https://github.com/ifzhang/FairMOT
공식 코드FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/ignc-research/habitatdyn
공식 코드HabitatDyn Dataset: Dynamic Object Detection to Kinematics Estimation
https://github.com/igor-morawski/nod
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.