Recognizing out-of-distribution (OOD) samples is critical for machine learning systems
deployed in the open world. The vast majority of OOD detection methods are driven by a …

Autoregressive models and their sequential factorization of the data likelihood have recently
demonstrated great potential for image representation and synthesis. Nevertheless, they …

Despite recent research advancements in reconstructing clothed humans from a single
image, accurately restoring the “unseen regions” with high-level details remains an …

Recent Vision-Language Pre-trained (VLP) models based on dual encoder have attracted
extensive attention from academia and industry due to their superior performance on various …

Describing soundscapes in sentences allows better understanding of the acoustic scene
than a single label indicating the acoustic scene class or a set of audio tags indicating the …

Image captioning is oriented towards describing an image with the best possible use of
words that can provide a semantic, relatable meaning of the scenario inscribed. Different …

Image captioning studies heavily rely on automatic evaluation metrics such as BLEU and
METEOR. However, such n-gram-based metrics have been shown to correlate poorly with …

Pretraining large models on generous multi-modal corpora has accelerated the
development of visual-linguistic (VL) representation and achieved great success on various …

Developers of text generation models rely on automated evaluation metrics as a stand-in for
slow and expensive manual evaluations. However, image captioning metrics have struggled …

Several services for people with visual disabilities have emerged recently due to
achievements in Assistive Technologies and Artificial Intelligence areas. Despite the growth …