The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range
dependencies, via aggregating query-specific global context to each query position. However, …

Recent studies reveal that a deep neural network can learn transferable features which
generalize well to novel tasks for domain adaptation. However, as deep features eventually …

This paper presents a new vision Transformer, called Swin Transformer, that capably serves
as a general-purpose backbone for computer vision. Challenges in adapting Transformer …

The vision community is witnessing a modeling shift from CNNs to Transformers, where
pure Transformer architectures have attained top accuracy on the major video recognition …

We launch EVA, a vision-centric foundation model to explore the limits of visual representation
at scale using only publicly accessible data. EVA is a vanilla ViT pre-trained to reconstruct …

We introduce a new pre-trainable generic representation for visual-linguistic tasks, called
Visual-Linguistic BERT (VL-BERT for short). VL-BERT adopts the simple yet powerful …

Gelatinous underwater invertebrates such as jellyfish have organs that are transparent,
stretchable, touch-sensitive and self-healing, which allow the creatures to navigate, camouflage …

DOI: 10.1002/adma. 201605099 great promise in stretchable ionic devices, such as
electrically activated, soft, transparent actuators and loudspeakers [37] and ionic skins that can …

The introduction of intelligent devices with short range wireless communication techniques
has motivated the development of Mobile Ad hoc NETworks (MANETs) during the last few …

We present techniques for scaling Swin Transformer [??] up to 3 billion parameters and
making it capable of training with images of up to 1,536 x1, 536 resolution. By scaling up …