Visual prompt engineering is a fundamental methodology in the field of visual and image
artificial general intelligence. As the development of large vision models progresses, the …

In the past year, MultiModal Large Language Models (MM-LLMs) have undergone
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …

This work investigates a simple yet powerful adapter for Vision Transformer (ViT). Unlike
recent visual transformers that introduce vision-specific inductive biases into their …

The Segment Anything Model (SAM) has recently gained popularity in the field of image
segmentation due to its impressive capabilities in various segmentation tasks and its prompt …

Visible-modal object tracking gives rise to a series of downstream multi-modal tracking
tributaries. To inherit the powerful representations of the foundation model, a natural modus …

Existing fine-tuning methods either tune all parameters of the pre-trained model (full fine-
tuning), which is not efficient, or only tune the last linear layer (linear probing), which suffers …

Deep models, eg, CNNs and Vision Transformers, have achieved impressive achievements
in many vision tasks in the closed world. However, novel classes emerge from time to time in …

The recent wave of AI-generated content has witnessed the great development and success
of Text-to-Image (T2I) technologies. By contrast Text-to-Video (T2V) still falls short of …

We consider the generic problem of detecting low-level structures in images, which includes
segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow …

Recently, growing interest has been aroused in extending the multimodal capability of large
language models (LLMs), eg, vision-language (VL) learning, which is regarded as the next …