prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the siaMAC+QE* model in the CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples paper on the Par106k dataset? | mAP |
What metrics were used to measure the R-MAC model in the Particular object retrieval with integral max-pooling of CNN activations paper on the Par106k dataset? | mAP |
What metrics were used to measure the Hypergraph propagation+Community selection model in the Hypergraph Propagation and Community Selection for Objects Retrieval paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the Token model in the Learning Token-based Representation for Image Retrieval paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the FIRe model in the Learning Super-Features for Image Retrieval paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the DELG+ α QE reranking + RRT reranking model in the Instance-level Image Retrieval using Reranking Transformers paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HOW model in the Learning and aggregating deep local descriptors for instance-level recognition paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the ResNet101+ArcFace GLDv2-train-clean model in the Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the DELF–HQE+SP model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–HQE+SP model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the DELF–ASMK*+SP model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–HQE model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HED-N-GAN model in the Dark Side Augmentation: Generating Diverse Night Examples for Metric Learning paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the R–GeM model in the Fine-tuning CNN Image Retrieval with No Human Annotation paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the R–R-MAC model in the End-to-end Learning of Deep Visual Representations for Image Retrieval paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–ASMK*+SP model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–ASMK* model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–SMK*+SP model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–SMK* model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the R – [O] –CroW model in the Cross-dimensional Weighting for Aggregated Deep Convolutional Features paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the R – [O] –MAC model in the Particular object retrieval with integral max-pooling of CNN activations paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the R – [O] –SPoC model in the Aggregating Deep Convolutional Features for Image Retrieval paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–VLAD model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the ROxford (Medium) dataset? | mAP |
What metrics were used to measure the CGD (MG/SG) model in the Combination of Multiple Global Descriptors for Image Retrieval paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the ProxyNCA++ model in the ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the NormSoftmax2048 (ResNet-50) model in the Classification is a Strong Baseline for Deep Metric Learning paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the MES-Loss model in the MES-Loss: Mutually equidistant separation metric learning loss function paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the Margin model in the Sampling Matters in Deep Embedding Learning paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the MS512 model in the Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the EPSHN512 model in the Improved Embeddings with Easy Positive Triplet Mining paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the HTL model in the Deep Metric Learning with Hierarchical Triplet Loss paper on the CARS196 dataset? | R@1, R@8 |
What metrics were used to measure the SSAN model in the Semantically Self-Aligned Network for Text-to-Image Part-aware Person Re-identification paper on the ICFG-PEDES dataset? | rank-1 |
What metrics were used to measure the CGD (SG/GS) model in the Combination of Multiple Global Descriptors for Image Retrieval paper on the In-Shop dataset? | R@1 |
What metrics were used to measure the Cross-Batch Memory model in the Cross-Batch Memory for Embedding Learning paper on the In-Shop dataset? | R@1 |
What metrics were used to measure the ProxyNCA++ model in the ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis paper on the In-Shop dataset? | R@1 |
What metrics were used to measure the MS512 model in the Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning paper on the In-Shop dataset? | R@1 |
What metrics were used to measure the NormSoftmax2048 (ResNet-50) model in the Classification is a Strong Baseline for Deep Metric Learning paper on the In-Shop dataset? | R@1 |
What metrics were used to measure the EPSHN512 model in the Improved Embeddings with Easy Positive Triplet Mining paper on the In-Shop dataset? | R@1 |
What metrics were used to measure the ABE-8 model in the Attention-based Ensemble for Deep Metric Learning paper on the In-Shop dataset? | R@1 |
What metrics were used to measure the IME layer model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Paris6k dataset? | mAP |
What metrics were used to measure the GNN-Reranking model in the Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective paper on the Paris6k dataset? | mAP |
What metrics were used to measure the BLIP-2 ViT-G (fine-tuned) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the COCO dataset? | recall@1, recall@5, Recall@10, QPS |
What metrics were used to measure the VisualSparta model in the VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words paper on the COCO dataset? | recall@1, recall@5, Recall@10, QPS |
What metrics were used to measure the BLIP-2 ViT-L (fine-tuned) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the COCO dataset? | recall@1, recall@5, Recall@10, QPS |
What metrics were used to measure the FLAVA (zero-shot) model in the FLAVA: A Foundational Language And Vision Alignment Model paper on the COCO dataset? | recall@1, recall@5, Recall@10, QPS |
What metrics were used to measure the CLIP (zero-shot) model in the FLAVA: A Foundational Language And Vision Alignment Model paper on the COCO dataset? | recall@1, recall@5, Recall@10, QPS |
What metrics were used to measure the Oscar model in the Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks paper on the COCO dataset? | recall@1, recall@5, Recall@10, QPS |
What metrics were used to measure the DTQ model in the Deep Triplet Quantization paper on the NUS-WIDE dataset? | MAP |
What metrics were used to measure the MultiGrain R50 @ 800 model in the MultiGrain: a unified image embedding for classes and instances paper on the INRIA Holidays dataset? | Mean mAP |
What metrics were used to measure the MultiGrain R50 @ 500 model in the MultiGrain: a unified image embedding for classes and instances paper on the INRIA Holidays dataset? | Mean mAP |
What metrics were used to measure the Hypergraph propagation model in the Hypergraph Propagation and Community Selection for Objects Retrieval paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the Token model in the Learning Token-based Representation for Image Retrieval paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the DELG+ α QE reranking + RRT reranking model in the Instance-level Image Retrieval using Reranking Transformers paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the FIRe model in the Learning Super-Features for Image Retrieval paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the ResNet101+ArcFace GLDv2-train-clean model in the Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the DELF–HQE+SP model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HOW model in the Learning and aggregating deep local descriptors for instance-level recognition paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the R–R-MAC model in the Particular object retrieval with integral max-pooling of CNN activations paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the R–GeM model in the Fine-tuning CNN Image Retrieval with No Human Annotation paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the DELF–ASMK*+SP model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HED-N-GAN model in the Dark Side Augmentation: Generating Diverse Night Examples for Metric Learning paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the R – [O] –CroW model in the Cross-dimensional Weighting for Aggregated Deep Convolutional Features paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–HQE+SP model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the R – [O] –SPoC model in the Aggregating Deep Convolutional Features for Image Retrieval paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–HQE model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the R – [O] –MAC model in the Particular object retrieval with integral max-pooling of CNN activations paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–ASMK*+SP model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–ASMK* model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–SMK*+SP model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–SMK* model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the HesAff–rSIFT–VLAD model in the Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking paper on the RParis (Medium) dataset? | mAP |
What metrics were used to measure the DINOv2 distilled (ViT-L/14 frozen) model in the DINOv2: Learning Robust Visual Features without Supervision paper on the AmsterTime dataset? | mAP |
What metrics were used to measure the DINOv2 (ViT-g/14 frozen) model in the DINOv2: Learning Robust Visual Features without Supervision paper on the AmsterTime dataset? | mAP |
What metrics were used to measure the DINOv2 distilled (ViT-B/14 frozen) model in the DINOv2: Learning Robust Visual Features without Supervision paper on the AmsterTime dataset? | mAP |
What metrics were used to measure the DINOv2 distilled (ViT-S/14 frozen) model in the DINOv2: Learning Robust Visual Features without Supervision paper on the AmsterTime dataset? | mAP |
What metrics were used to measure the AP-GeM (ResNet-101) model in the AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift paper on the AmsterTime dataset? | mAP |
What metrics were used to measure the WIT-ALL model in the WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning paper on the WIT dataset? | R@1, R@5 |
What metrics were used to measure the CC (Conceptual Captions) model in the WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning paper on the WIT dataset? | R@1, R@5 |
What metrics were used to measure the Candidate Set Re-ranking model in the Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encoder paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the RUTIR (BLIP B/16) model in the Ranking-aware Uncertainty for Text-guided Image Retrieval paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the CASE model in the Data Roaming and Early Fusion for Composed Image Retrieval paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the CoVR-BLIP model in the CoVR: Learning Composed Video Retrieval from Web Video Captions paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the CLIP4Cir (v3) model in the Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the RUTIR (CLIP ResNet50) model in the Ranking-aware Uncertainty for Text-guided Image Retrieval paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the Css-Net model in the Relieving Triplet Ambiguity: Consensus Network for Language-Guided Image Retrieval paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the MUR (4*ResNet50) model in the Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the CLIP4Cir (v2) model in the Conditioned and Composed Image Retrieval Combining and Partially Fine-Tuning CLIP-Based Features paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the MUR model in the Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the CLIP4Cir model in the Effective Conditioned and Composed Image Retrieval Combining CLIP-Based Features paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the RTIC-GCN model in the RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Network paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the CoSMo model in the CoSMo: Content-Style Modulation for Image Retrieval With Text Feedback paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the CurlingNet model in the CurlingNet: Compositional Learning between Images and Text for Fashion IQ Data paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the VAL w/ GloVe model in the Image Search With Text Feedback by Visiolinguistic Attention Learning paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the ComposeAE model in the Compositional Learning of Image-Text Query for Image Retrieval paper on the Fashion IQ dataset? | (Recall@10+Recall@50)/2 |
What metrics were used to measure the OPT model in the OPT: Omni-Perception Pre-Trainer for Cross-Modal Understanding and Generation paper on the Localized Narratives dataset? | Text-to-image R@1, Text-to-image R@10, Text-to-image R@5 |
What metrics were used to measure the monoT5-3B (zero-shot) model in the Document Ranking with a Pretrained Sequence-to-Sequence Model paper on the TREC Robust04 dataset? | nDCG@20, MAP, P@20 |
What metrics were used to measure the PARADE(ELECTRA) model in the PARADE: Passage Representation Aggregation for Document Reranking paper on the TREC Robust04 dataset? | nDCG@20, MAP, P@20 |
What metrics were used to measure the CEDR-KNRM model in the CEDR: Contextualized Embeddings for Document Ranking paper on the TREC Robust04 dataset? | nDCG@20, MAP, P@20 |
What metrics were used to measure the PARADE(BERT) model in the PARADE: Passage Representation Aggregation for Document Reranking paper on the TREC Robust04 dataset? | nDCG@20, MAP, P@20 |
What metrics were used to measure the BERT-MaxP model in the Deeper Text Understanding for IR with Contextual Neural Language Modeling paper on the TREC Robust04 dataset? | nDCG@20, MAP, P@20 |
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