GCAM: Gaussian and causal-attention model of food fine-grained recognition

arXiv:2403.12109v1 Announce Type: new
Abstract: Currently, most food recognition relies on deep learning for category classification. However, these approaches struggle to effectively distinguish between visually similar food samples, highlighting the pressing need to address fine-grained issues in food recognition. To mitigate these challenges, we propose the adoption of a Gaussian and causal-attention model for fine-grained object recognition.In particular, we train to obtain Gaussian features over target regions, followed by the extraction of fine-grained features from the objects, thereby enhancing the …

abstract adoption arxiv attention causal challenges classification cs.ai cs.cv cs.lg deep learning fine-grained food highlighting however recognition samples struggle type