prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the ROADMAP (Deit-B) model in the Robust and Decomposable Average Precision for Image Retrieval paper on the CUB-200-2011 dataset? | R@1, R@2, R@4, R@8 |
What metrics were used to measure the ProxyNCA++ model in the ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis paper on the CUB-200-2011 dataset? | R@1, R@2, R@4, R@8 |
What metrics were used to measure the ROADMAP (ResNet-50) model in the Robust and Decomposable Average Precision for Image Retrieval paper on the CUB-200-2011 dataset? | R@1, R@2, R@4, 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 CUB-200-2011 dataset? | R@1, R@2, R@4, 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 CUB-200-2011 dataset? | R@1, R@2, R@4, 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 CUB-200-2011 dataset? | R@1, R@2, R@4, R@8 |
What metrics were used to measure the EPSHN512 model in the Improved Embeddings with Easy Positive Triplet Mining paper on the CUB-200-2011 dataset? | R@1, R@2, R@4, R@8 |
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 without fine-tuning dataset? | Average mAP |
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 CIRR dataset? | (Recall@5+Recall_subset@1)/2 |
What metrics were used to measure the CASE (Pre-trained on LaSCo.Ca) model in the Data Roaming and Early Fusion for Composed Image Retrieval paper on the CIRR dataset? | (Recall@5+Recall_subset@1)/2 |
What metrics were used to measure the CASE model in the Data Roaming and Early Fusion for Composed Image Retrieval paper on the CIRR dataset? | (Recall@5+Recall_subset@1)/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 CIRR dataset? | (Recall@5+Recall_subset@1)/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 CIRR dataset? | (Recall@5+Recall_subset@1)/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 CIRR dataset? | (Recall@5+Recall_subset@1)/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 CIRR dataset? | (Recall@5+Recall_subset@1)/2 |
What metrics were used to measure the CIRPLANT model in the Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models paper on the CIRR dataset? | (Recall@5+Recall_subset@1)/2 |
What metrics were used to measure the ARTEMIS model in the ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity paper on the CIRR dataset? | (Recall@5+Recall_subset@1)/2 |
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 Google Landmarks Dataset v2 (retrieval, testing) dataset? | mAP@100 |
What metrics were used to measure the Offline Diffusion model in the Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the CNN+IME layer model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the DELF+FT+ATT+DIR+QE model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the DIR+QE* model in the Deep Image Retrieval: Learning global representations for image search paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the DELF+FT+ATT model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the IME model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf5k dataset? | MAP |
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 Oxf5k dataset? | MAP |
What metrics were used to measure the PCA [51] model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the IsoMap [32] model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the SIFT+IME layer model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the LLE [33] model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf5k dataset? | MAP |
What metrics were used to measure the ERNIE-ViL2.0 model in the ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training paper on the AIC-ICC dataset? | Recall@1, Recall@10, Recall@5 |
What metrics were used to measure the CMCL model in the WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training paper on the AIC-ICC dataset? | Recall@1, Recall@10, Recall@5 |
What metrics were used to measure the Offline Diffusion model in the Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing paper on the Oxf105k dataset? | MAP |
What metrics were used to measure the DELF+FT+ATT+DIR+QE model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Oxf105k dataset? | MAP |
What metrics were used to measure the DIR+QE* model in the Deep Image Retrieval: Learning global representations for image search paper on the Oxf105k dataset? | MAP |
What metrics were used to measure the CNN+IME layer model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf105k dataset? | MAP |
What metrics were used to measure the DELF+FT+ATT model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Oxf105k dataset? | MAP |
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 Oxf105k dataset? | MAP |
What metrics were used to measure the R-MAC+R+QE model in the Particular object retrieval with integral max-pooling of CNN activations paper on the Oxf105k 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 Oxf105k dataset? | MAP |
What metrics were used to measure the SIFT+IME layer model in the Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval paper on the Oxf105k 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 24/7 Tokyo dataset? | mAP |
What metrics were used to measure the CIConv model in the Zero-Shot Day-Night Domain Adaptation with a Physics Prior paper on the 24/7 Tokyo dataset? | mAP |
What metrics were used to measure the CLAHE model in the No Fear of the Dark: Image Retrieval under Varying Illumination Conditions paper on the 24/7 Tokyo dataset? | mAP |
What metrics were used to measure the CN-CLIP (ViT-H/14) model in the Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the CN-CLIP (ViT-L/14@336px) model in the Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the CN-CLIP (ViT-L/14) model in the Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the R2D2 (ViT-L/14) model in the CCMB: A Large-scale Chinese Cross-modal Benchmark paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the CN-CLIP (ViT-B/16) model in the Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the Wukong (ViT-L/14) model in the Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the CN-CLIP (RN50) model in the Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the R2D2 (ViT-B) model in the CCMB: A Large-scale Chinese Cross-modal Benchmark paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the Wukong (ViT-B/32) model in the Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark paper on the MUGE Retrieval dataset? | Mean Recall, R@1, R@10, R@5 |
What metrics were used to measure the RCCapsNet model in the Fashion Image Retrieval with Capsule Networks paper on the DeepFashion dataset? | Recall@20 |
What metrics were used to measure the CMCL model in the WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training paper on the RUC-CAS-WenLan dataset? | Recall@1, Recall@10, Recall@5 |
What metrics were used to measure the SuperGlobal model in the Global Features are All You Need for Image Retrieval and Reranking paper on the RParis (Hard) dataset? | 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 (Hard) dataset? | mAP |
What metrics were used to measure the Token model in the Learning Token-based Representation for Image Retrieval paper on the RParis (Hard) 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 (Hard) 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 (Hard) dataset? | mAP |
What metrics were used to measure the FIRe model in the Learning Super-Features for Image Retrieval paper on the RParis (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) dataset? | mAP |
What metrics were used to measure the R – [O] –SPoC model in the Aggregating Local Deep Features for Image Retrieval paper on the RParis (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) 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 (Hard) dataset? | mAP |
What metrics were used to measure the PaCE model in the PaCE: Unified Multi-modal Dialogue Pre-training with Progressive and Compositional Experts paper on the PhotoChat dataset? | R1, R@10, R@5, Sum(R@1,5,10) |
What metrics were used to measure the VLMo model in the VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts paper on the PhotoChat dataset? | R1, R@10, R@5, Sum(R@1,5,10) |
What metrics were used to measure the ViLT model in the ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision paper on the PhotoChat dataset? | R1, R@10, R@5, Sum(R@1,5,10) |
What metrics were used to measure the SCAN model in the Stacked Cross Attention for Image-Text Matching paper on the PhotoChat dataset? | R1, R@10, R@5, Sum(R@1,5,10) |
What metrics were used to measure the DE++ model in the PhotoChat: A Human-Human Dialogue Dataset with Photo Sharing Behavior for Joint Image-Text Modeling paper on the PhotoChat dataset? | R1, R@10, R@5, Sum(R@1,5,10) |
What metrics were used to measure the Ranknet model in the Retrieving Similar E-Commerce Images Using Deep Learning paper on the street2shop - topwear dataset? | Accuracy |
What metrics were used to measure the MILDNet model in the MILDNet: A Lightweight Single Scaled Deep Ranking Architecture paper on the street2shop - topwear dataset? | Accuracy |
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 Oxford5k dataset? | mAP |
What metrics were used to measure the Identification+Verification model in the A Discriminatively Learned CNN Embedding for Person Re-identification paper on the Oxford5k dataset? | mAP |
What metrics were used to measure the FETA's CLIP-MIL (Many-Shot Image-to-text) model in the FETA: Towards Specializing Foundation Models for Expert Task Applications paper on the FETA Car-Manuals dataset? | R@1, R@10, R@5 |
What metrics were used to measure the Offline Diffusion model in the Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing paper on the Par6k dataset? | mAP |
What metrics were used to measure the DELF+FT+ATT+DIR+QE model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Par6k dataset? | mAP |
What metrics were used to measure the DIR+QE* model in the Deep Image Retrieval: Learning global representations for image search paper on the Par6k dataset? | mAP |
What metrics were used to measure the R-MAC+R+QE model in the Particular object retrieval with integral max-pooling of CNN activations paper on the Par6k dataset? | mAP |
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 Par6k dataset? | mAP |
What metrics were used to measure the DELF+FT+ATT model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Par6k 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 Par6k dataset? | mAP |
What metrics were used to measure the SwinV2 model in the Patent image retrieval using transformer-based deep metric learning paper on the DeepPatent dataset? | mean average precision |
What metrics were used to measure the EffNet model in the Patent Image Retrieval Using Cross-entropy-based Metric Learning paper on the DeepPatent dataset? | mean average precision |
What metrics were used to measure the Res50 model in the DeepPatent: Large scale patent drawing recognition and retrieval paper on the DeepPatent dataset? | mean average precision |
What metrics were used to measure the Offline Diffusion model in the Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing paper on the Par106k dataset? | mAP |
What metrics were used to measure the DELF+FT+ATT+DIR+QE model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Par106k dataset? | mAP |
What metrics were used to measure the DIR+QE* model in the Deep Image Retrieval: Learning global representations for image search paper on the Par106k dataset? | mAP |
What metrics were used to measure the DELF+FT+ATT model in the Large-Scale Image Retrieval with Attentive Deep Local Features paper on the Par106k dataset? | mAP |
What metrics were used to measure the R-MAC+R+QE model in the Particular object retrieval with integral max-pooling of CNN activations paper on the Par106k dataset? | mAP |
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