Recently, the rise of large-scale vision-language pretrained models like CLIP, coupled with
the technology of Parameter-Efficient FineTuning (PEFT), has captured substantial attraction …

Recently, the rise of large-scale vision-language pretrained models like CLIP, coupled with
the technology of Parameter-Efficient FineTuning (PEFT), has captured substantial attraction …

Existing scene text spotters are designed to locate and transcribe texts from images.
However, it is challenging for a spotter to achieve precise detection and recognition of scene …

Recognizing video actions in the wild is challenging for visual control systems. In-the-wild
videos show actions not seen in training data, recorded from various angles and scenes with …

The canonical video action recognition methods usually label categories with numbers or
one-hot vectors and train neural networks to classify a fixed set of predefined categories …

We introduce a new task called Referring Atomic Video Action Recognition (RAVAR), aimed
at identifying atomic actions of a particular person based on a textual description and the …

In the context of escalating safety concerns across various domains, the tasks of Video
Anomaly Detection (VAD) and Video Anomaly Recognition (VAR) have emerged as critically …

Fused Magnesium Furnace (FMF) is a crucial industrial equipment in the production of
magnesia, and anomaly detection plays a pivotal role in ensuring its efficient, stable, and …

This paper introduces 'SkeletonCLIP++', an extension of our prior work in human action
recognition, emphasizing the use of semantic information beyond traditional label-based …

Recently, prompt-based methods have emerged as a new alternativeparameter-efficient fine-
tuning'paradigm, which only fine-tunes a small number of additional parameters while …