Food-101

Overview edit

Variants: Food-101, food101

Associated Benchmarks

This dataset is used in 10 benchmarks:

• Zero-Shot Learning - Metrics: Accuracy
• Neural Architecture Search - Metrics: Accuracy (%), FLOPS, PARAMS, Accuracy (% )
• Image Clustering - Metrics: Accuracy
• Image Compression - Metrics: Bit rate
• Image Classification - Metrics: Accuracy (%)
• Fine-Grained Image Classification - Metrics: Accuracy, FLOPS, PARAMS, Top 1 Accuracy
• Document Text Classification - Metrics: Accuracy (%)
• Zero-Shot Transfer Image Classification - Metrics: Top 1 Accuracy
• Prompt Engineering - Metrics: Harmonic mean
• Multimodal Text and Image Classification - Metrics: Accuracy (%)

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics (2025) -
• SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning (2025) -
• MMRL++: Parameter-Efficient and Interaction-Aware Representation Learning for Vision-Language Models (2025) -
• MMRL: Multi-Modal Representation Learning for Vision-Language Models (2025) -
• HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling (2024) -
• Let Go of Your Labels with Unsupervised Transfer (2024) -
• Label Propagation for Zero-shot Classification with Vision-Language Models (2024) -
• Prompt Learning via Meta-Regularization (2024) -
• PromptKD: Unsupervised Prompt Distillation for Vision-Language Models (2024) -
• EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters (2024) -
• InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks (2023) -
• Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models (2023) -
• DePT: Decoupled Prompt Tuning (2023) -
• Read-only Prompt Optimization for Vision-Language Few-shot Learning (2023) -
• Self-regulating Prompts: Foundational Model Adaptation without Forgetting (2023) -
• Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture (2023) -
• Consistency-guided Prompt Learning for Vision-Language Models (2023) -
• Your Diffusion Model is Secretly a Zero-Shot Classifier (2023) -
• EVA-CLIP: Improved Training Techniques for CLIP at Scale (2023) -
• The effectiveness of MAE pre-pretraining for billion-scale pretraining (2023) -