We propose Make-A-Video -- an approach for directly translating the tremendous recent
progress in Text-to-Image (T2I) generation to Text-to-Video (T2V). Our intuition is simple: learn …

Despite the success of the deep neural networks, it remains challenging to effectively build a
system for long-tail visual recognition tasks. To address this problem, we first investigate the …

Low levels of reactive oxygen species (ROS) are crucial for maintaining cancer stem cells (CSCs)
and their ability to resist therapy, but the ROS regulatory mechanisms in CSCs …

RNN-based approaches have achieved outstanding performance on action recognition with
skeleton inputs. Currently these methods limit their inputs to coordinates of joints and …

Contrastive language-image pretraining has shown great success in learning visual-textual
joint representation from web-scale data, demonstrating remarkable “zero-shot” …

The anti-hyperglycemic effect of metformin is believed to be caused by its direct action on
signaling processes in hepatocytes, leading to lower hepatic gluconeogenesis. Recently, …

Large vision-language models (VLMs) have recently achieved remarkable progress,
exhibiting impressive multimodal perception and reasoning abilities. However, effectively …

We address the problem of retrieving a specific moment from an untrimmed video by a
query sentence. This is a challenging problem because a target moment may take place in …

Few-shot semantic segmentation aims to learn to segment new object classes with only a
few annotated examples, which has a wide range of real-world applications. Most existing …

We introduce InternLM-XComposer2, a cutting-edge vision-language model excelling in free-form
text-image composition and comprehension. This model goes beyond conventional …