Astounding results from Transformer models on natural language tasks have intrigued the
vision community to study their application to computer vision problems. Among their salient …

The POSTER has achieved SOTA performance in facial expression recognition (FER) by
effectively combining facial landmarks and image features through its two-stream pyramid …

With the success of Vision Transformers (ViTs) in computer vision tasks, recent arts try to
optimize the performance and complexity of ViTs to enable efficient deployment on mobile …

Abstract Vision Transformers (ViT) have shown rapid progress in computer vision tasks,
achieving promising results on various benchmarks. However, due to the massive number of …

We consider two biologically plausible structures, the Spiking Neural Network (SNN) and the
self-attention mechanism. The former offers an energy-efficient and event-driven paradigm …

Abstract We present Neighborhood Attention (NA), the first efficient and scalable sliding
window attention mechanism for vision. NA is a pixel-wise operation, localizing self attention …

Abstract Visual Place Recognition (VPR) estimates the location of query images by matching
them with images in a reference database. Conventional methods generally adopt …

Vision transformers have become popular as a possible substitute to convolutional neural
networks (CNNs) for a variety of computer vision applications. These transformers, with their …

Visual Geo-localization (VG) is the task of estimating the position where a given photo was
taken by comparing it with a large database of images of known locations. To investigate …

Renal failure, a public health concern, and the scarcity of nephrologists around the globe
have necessitated the development of an AI-based system to auto-diagnose kidney …