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 …

Plant diseases have an important impact on agricultural production and economic efficiency.
Timely detection of crop diseases and accurate determination of diseases are important for …

Fine-grained visual classification (FGVC) which aims at recognizing objects from
subcategories is a very challenging task due to the inherently subtle inter-class differences …

Fine-grained bird image classification (FBIC) is not only meaningful for endangered bird
observation and protection but also a prevalent task for image classification in multimedia …

Inspired by the human cognitive system, attention is a mechanism that imitates the human
cognitive awareness about specific information, amplifying critical details to focus more on …

High spatial resolution (HSR) remote sensing images contain complex foreground-
background relationships, which makes the remote sensing land cover segmentation a …

Recent progress on fine-grained visual recognition and visual question answering has
featured Bilinear Pooling, which effectively models the 2nd order interactions across multi …

Fine-grained classification is a challenging problem, due to subtle differences among highly-
confused categories. Most approaches address this difficulty by learning discriminative …

Delicate feature representation about object parts plays a critical role in fine-grained
recognition. For example, experts can even distinguish fine-grained objects relying only on …

Vision-based Automated Vehicle Recognition (VAVR) has attracted considerable attention
recently. Particularly given the reliance on emerging deep learning methods, which have …