5 papers · 1 filter
DishSeg24k: A Large-Scale Benchmark for Food Segmentation with Stochastic Expert Decoding
Yilin Wang, Haochen Shi, Guanyu Chen +4
Food segmentation is essential for applications such as intelligent catering, dietary assessment, and recommendation. However, existing benchmarks fail to capture the complexity of…
Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition
Xinda Liu, Qinyu Zhang, Weiqing Min +2
Fine-grained image recognition poses a significant challenge due to the substantial expertise and effort required for manual annotation. Vision-language models (VLMs) like CLIP pro…
RFHNet: Relational and Frequency-Aware Hashing Network for Large-Scale Fine-Grained Food Image Retrieval
Junsong Wang, Weiqing Min, Guorui Sheng +3
Fine-grained food image retrieval is a key task in computational gastronomy, with applications in food traceability, dietary monitoring, and smart catering systems. Although hashin…
OmniFood8K: Single-Image Nutrition Estimation via Hierarchical Frequency-Aligned Fusion
Dongjian Yu, Weiqing Min, Qian Jiang +3
Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datasets primarily focus on Wester…
Synthesizing Knowledge-enhanced Features for Real-world Zero-shot Food Detection
Pengfei Zhou, Weiqing Min, Jiajun Song +2
Food computing brings various perspectives to computer vision like vision-based food analysis for nutrition and health. As a fundamental task in food computing, food detection need…