Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …

Audio-visual learning, aimed at exploiting the relationship between audio and visual
modalities, has drawn considerable attention since deep learning started to be used …

Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer
vision and pattern recognition, and underpins a diverse set of real-world applications. The …

Fine-grained visual classification (FGVC) is much more challenging than traditional
classification tasks due to the inherently subtle intra-class object variations. Recent works …

Generalized zero-shot learning (GZSL) requires a classifier trained on seen classes that can
recognize objects from both seen and unseen classes. Due to the absence of unseen …

Few-shot learning for fine-grained image classification has gained recent attention in
computer vision. Among the approaches for few-shot learning, due to the simplicity and …

Whether what you see in Figure 1 is a" flamingo" or a" bird", is the question we ask in this
paper. While fine-grained visual classification (FGVC) strives to arrive at the former, for the …

Fine-grained object recognition aims to learn effective features that can identify the subtle
differences between visually similar objects. Most of the existing works tend to amplify …

Fine-grained visual classification (FGVC) is much more challenging than traditional
classification tasks due to the inherently subtle intra-class object variations. Recent works …

Semantic patterns of fine-grained objects are determined by subtle appearance difference of
local parts, which thus inspires a number of part-based methods. However, due to …