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홈뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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  4. Vehicle Re Identification On Vehicleid Large

Vehicle Re Identification On Vehicleid Large

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이 벤치마크에서 각 모델의 성능 결과

모델 이름
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Paper TitleRepository
PNP Loss93.296.6Rethinking the Optimization of Average Precision: Only Penalizing Negative Instances before Positive Ones is Enough
Recall@k Surrogate loss (ViT-B/16)94.797.1Recall@k Surrogate Loss with Large Batches and Similarity Mixup
ANet80.594.6AttributeNet: Attribute Enhanced Vehicle Re-Identification-
Smooth-AP91.996.2Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval
QD-DLF--Vehicle Re-identification Using Quadruple Directional Deep Learning Features-
CAL75.1-Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
MSINet (2.3M w/o RK)77.991.7MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID
RPTM92.996.3Relation Preserving Triplet Mining for Stabilising the Triplet Loss in Re-identification Systems
Recall@k Surrogate loss (ResNet-50)93.896.6Recall@k Surrogate Loss with Large Batches and Similarity Mixup
vehiclenet79.46-VehicleNet: Learning Robust Feature Representation for Vehicle Re-identification-
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뉴스튜토리얼데이터셋백과사전

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