Large AI models, or foundation models, are models recently emerging with massive scales
both parameter-wise and data-wise, the magnitudes of which can reach beyond billions …

This article discusses the opportunities, applications and future directions of large-scale
pretrained models, ie, foundation models, which promise to significantly improve the …

The recent breakthroughs in natural language processing for model pretraining on large
quantities of data have opened the way for similar foundation models in computer vision …

Scaling up neural networks has led to remarkable performance across a wide range of
tasks. Moreover, performance often follows reliable scaling laws as a function of training set …

Large language models (LLMs) have notably accelerated progress towards artificial general
intelligence (AGI), with their impressive zero-shot capacity for user-tailored tasks, endowing …

In this paper, we initiate an attempt of developing an end-to-end chat-centric video
understanding system, coined as VideoChat. It integrates video foundation models and …

Recently the state space models (SSMs) with efficient hardware-aware designs, ie, the
Mamba deep learning model, have shown great potential for long sequence modeling …

In this paper, we provide the observation that too few queries assigned as positive samples
in DETR with one-to-one set matching leads to sparse supervision on the encoder's output …

We present a novel bird's-eye-view (BEV) detector with perspective supervision, which
converges faster and better suits modern image backbones. Existing state-of-the-art BEV …

We launch EVA-02, a next-generation Transformer-based visual representation pre-trained
to reconstruct strong and robust language-aligned vision features via masked image …