prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the ResNet50 (128) + MIC model in the MIC: Mining Interclass Characteristics for Improved Metric Learning paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the BN-Inception + Group Loss model in the The Group Loss for Deep Metric Learning paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the BN-Inception + SoftTriple model in the SoftTriple Loss: Deep Metric Learning Without Triplet Sampling paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the EPSHN(512) model in the Improved Embeddings with Easy Positive Triplet Mining paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the Gradient Surgery model in the Dissecting the impact of different loss functions with gradient surgery paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the ResNet-50 + Margin model in the Sampling Matters in Deep Embedding Learning paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the HDC model in the Hard-Aware Deeply Cascaded Embedding paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the ABE-8-512 model in the Attention-based Ensemble for Deep Metric Learning paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the PDDM Quadruplet model in the Local Similarity-Aware Deep Feature Embedding paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the SCT(64) model in the Hard negative examples are hard, but useful paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the EPSHN(64) model in the Improved Embeddings with Easy Positive Triplet Mining paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the GoogLeNet + HDML model in the Hardness-Aware Deep Metric Learning paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the HAPPIER model in the Hierarchical Average Precision Training for Pertinent Image Retrieval paper on the DyML-Vehicle dataset? | Average-mAP |
What metrics were used to measure the CSL model in the Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales paper on the DyML-Vehicle dataset? | Average-mAP |
What metrics were used to measure the Unicom+ViT-L@336px model in the Unicom: Universal and Compact Representation Learning for Image Retrieval paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the STIR model in the STIR: Siamese Transformer for Image Retrieval Postprocessing paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Recall@k Surrogate Loss (ViT-B/16) model in the Recall@k Surrogate Loss with Large Batches and Similarity Mixup paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ViT-Triplet model in the STIR: Siamese Transformer for Image Retrieval Postprocessing paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ROADMAP (DeiT-S) model in the Robust and Decomposable Average Precision for Image Retrieval paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Hyp-ViT model in the Hyperbolic Vision Transformers: Combining Improvements in Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Hyp-DINO model in the Hyperbolic Vision Transformers: Combining Improvements in Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Recall@k Surrogate Loss (ViT-B/32) model in the Recall@k Surrogate Loss with Large Batches and Similarity Mixup paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ROADMAP (ResNet-50) model in the Robust and Decomposable Average Precision for Image Retrieval paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the CCL (ResNet-50) model in the Center Contrastive Loss for Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Recall@k Surrogate Loss (ResNet-50) model in the Recall@k Surrogate Loss with Large Batches and Similarity Mixup paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Gradient Surgery model in the Dissecting the impact of different loss functions with gradient surgery paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the HAPPIER_F model in the Hierarchical Average Precision Training for Pertinent Image Retrieval paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the SCT(512) model in the Hard negative examples are hard, but useful paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet-50 + Metrix model in the It Takes Two to Tango: Mixup for Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet50 + Language model in the Integrating Language Guidance into Vision-based Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the NED model in the Calibrated neighborhood aware confidence measure for deep metric learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet-50 + Cross-Entropy model in the A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet50 + S2SD model in the S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the HAPPIER model in the Hierarchical Average Precision Training for Pertinent Image Retrieval paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet-50 + ProxyNCA++ model in the ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet50 + NIR model in the Non-isotropy Regularization for Proxy-based Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the MS + DAS (K=8) model in the DAS: Densely-Anchored Sampling for Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the BN-Inception + Proxy-Anchor model in the Proxy Anchor Loss for Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet50 + DiVA model in the DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet50 + AVSL model in the Attributable Visual Similarity Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Margin + DIML model in the Towards Interpretable Deep Metric Learning with Structural Matching paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Circle Loss model in the Circle Loss: A Unified Perspective of Pair Similarity Optimization paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the EPSHN(512) model in the Improved Embeddings with Easy Positive Triplet Mining paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the QB-Norm+RDML model in the Cross Modal Retrieval with Querybank Normalisation paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet50 (128) + MIC model in the MIC: Mining Interclass Characteristics for Improved Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the ResNet50 (128) + PADS model in the PADS: Policy-Adapted Sampling for Visual Similarity Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Group Loss model in the The Group Loss for Deep Metric Learning paper on the Stanford Online Products dataset? | R@1 |
What metrics were used to measure the Hyp-DINO model in the Hyperbolic Vision Transformers: Combining Improvements in Metric Learning paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the MS + DAS (K=8) model in the DAS: Densely-Anchored Sampling for Deep Metric Learning paper on the CUB-200-2011 dataset? | R@1 |
What metrics were used to measure the InvPT model in the InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding paper on the PASCAL Context dataset? | Mean Angle Error |
What metrics were used to measure the PolyMaX(ConvNeXt-L) model in the PolyMaX: General Dense Prediction with Mask Transformer paper on the NYU Depth v2 dataset? | % < 11.25, % < 22.5, % < 30, Mean Angle Error, RMSE |
What metrics were used to measure the iDisc model in the iDisc: Internal Discretization for Monocular Depth Estimation paper on the NYU Depth v2 dataset? | % < 11.25, % < 22.5, % < 30, Mean Angle Error, RMSE |
What metrics were used to measure the Bae et al. model in the Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation paper on the NYU Depth v2 dataset? | % < 11.25, % < 22.5, % < 30, Mean Angle Error, RMSE |
What metrics were used to measure the Floors are Flat model in the Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction paper on the NYU Depth v2 dataset? | % < 11.25, % < 22.5, % < 30, Mean Angle Error, RMSE |
What metrics were used to measure the X-TC (Cross-Task Consistency) model in the Robust Learning Through Cross-Task Consistency paper on the Taskonomy dataset? | L1 error |
What metrics were used to measure the Bae et al. model in the Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation paper on the ScanNetV2 dataset? | % < 11.25, % < 22.5, % < 30, Mean Angle Error |
What metrics were used to measure the Floors are Flat model in the Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction paper on the ScanNetV2 dataset? | % < 11.25, % < 22.5, % < 30, Mean Angle Error |
What metrics were used to measure the MSECNet model in the MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioning paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the Hsurf model in the HSurf-Net: Normal Estimation for 3D Point Clouds by Learning Hyper Surfaces paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the NeAF model in the NeAF: Learning Neural Angle Fields for Point Normal Estimation paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the GraphFit model in the GraphFit: Learning Multi-scale Graph-Convolutional Representation for Point Cloud Normal Estimation paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the AdaFit model in the AdaFit: Rethinking Learning-based Normal Estimation on Point Clouds paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the DeepFit model in the DeepFit: 3D Surface Fitting via Neural Network Weighted Least Squares paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the Iter-Net model in the Deep Iterative Surface Normal Estimation paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the Nesti-Net model in the Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks paper on the PCPNet dataset? | RMSE |
What metrics were used to measure the DSN model in the On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation paper on the NYU-Depth V2 Surface Normals dataset? | RMSE |
What metrics were used to measure the DiT-L (Cascade) model in the DiT: Self-supervised Pre-training for Document Image Transformer paper on the cTDaR dataset? | Weighted Average F1-score |
What metrics were used to measure the DiT-B (Cascade) model in the DiT: Self-supervised Pre-training for Document Image Transformer paper on the cTDaR dataset? | Weighted Average F1-score |
What metrics were used to measure the cascadetabnet model in the CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents paper on the ICDAR2013 dataset? | Avg F1 |
What metrics were used to measure the CDeCNet model in the CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images paper on the ICDAR2013 dataset? | Avg F1 |
What metrics were used to measure the TableNet model in the TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images paper on the ICDAR2013 dataset? | Avg F1 |
What metrics were used to measure the RetinaNet model in the Table Detection in the Wild: A Novel Diverse Table Detection Dataset and Method paper on the STDW dataset? | IoU, AP |
What metrics were used to measure the Selective Search model in the Table Detection in the Wild: A Novel Diverse Table Detection Dataset and Method paper on the STDW dataset? | IoU, AP |
What metrics were used to measure the Ensemble multilingual BERT model model in the The Inception Team at NSURL-2019 Task 8: Semantic Question Similarity in Arabic paper on the Q2Q Arabic Benchmark dataset? | F1 score |
What metrics were used to measure the Tha3aroon model in the Tha3aroon at NSURL-2019 Task 8: Semantic Question Similarity in Arabic paper on the Q2Q Arabic Benchmark dataset? | F1 score |
What metrics were used to measure the mBert model in the Deep Learning Models for Multilingual Hate Speech Detection paper on the Q2Q Arabic Benchmark dataset? | F1 score |
What metrics were used to measure the Ours model in the Multi-Source Fusion and Automatic Predictor Selection for Zero-Shot Video Object Segmentation paper on the YouTube dataset? | Average |
What metrics were used to measure the XMem (BL30K, MS) model in the XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model paper on the DAVIS-2017 (test-dev) dataset? | Mean Jaccard & F-Measure, Jaccard, F-measure |
What metrics were used to measure the XMem model in the XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model paper on the DAVIS-2017 (test-dev) dataset? | Mean Jaccard & F-Measure, Jaccard, F-measure |
What metrics were used to measure the XMem (BL30K,MS) model in the XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the XMem model in the XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the BATMAN model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the AOT model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the RPCMVOS model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the MobileVOS model in the MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the STCN model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the CFBI+ model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the SST model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the CFBI model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the YouTube-VOS 2019 dataset? | Mean Jaccard & F-Measure, Jaccard (Seen), Jaccard (Unseen), F-Measure (Seen), F-Measure (Unseen) |
What metrics were used to measure the ISVOS (BL30K, MS) model in the Look Before You Match: Instance Understanding Matters in Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the XMem (BL30K, MS) model in the XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the BATMAN (val) model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the STCN (val) model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the XMem model in the XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the MobileVOS (val) model in the MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the AOT (val) model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the LCM (val) model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the RPCMVOS (val) model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the KMN (val) model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
What metrics were used to measure the TransVOS (val) model in the BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation paper on the DAVIS 2016 dataset? | J&F, F-Score, Jaccard (Mean), mIoU |
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