Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of …
We present SegNeXt, a simple convolutional network architecture for semantic segmentation. Recent transformer-based models have dominated the field of se-mantic …
Q Yu, J He, X Deng, X Shen… - Advances in Neural …, 2024 - proceedings.neurips.cc
Open-vocabulary segmentation is a challenging task requiring segmenting and recognizing objects from an open set of categories in diverse environments. One way to address this …
Abstract Pretraining Vision Transformers (ViTs) has achieved great success in visual recognition. A following scenario is to adapt a ViT to various image and video recognition …
This work investigates a simple yet powerful adapter for Vision Transformer (ViT). Unlike recent visual transformers that introduce vision-specific inductive biases into their …
Z Zhao, H Bai, J Zhang, Y Zhang, S Xu… - Proceedings of the …, 2023 - openaccess.thecvf.com
Multi-modality (MM) image fusion aims to render fused images that maintain the merits of different modalities, eg, functional highlight and detailed textures. To tackle the challenge in …
This study proposes a novel general image fusion framework based on cross-domain long- range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …
Recent research on remote sensing object detection has largely focused on improving the representation of oriented bounding boxes but has overlooked the unique prior knowledge …
The current modus operandi in adapting pre-trained models involves updating all the backbone parameters, ie., full fine-tuning. This paper introduces Visual Prompt Tuning (VPT) …