Transformer 已成为自然语言处理中的主要模型,因为它们能够对大量数据进行预训练,然后通过微调转移到更小、更具体的任务。 Vision Transformer 第一次尝试将纯 Transformer 模型直接应用于图像作为输入,表明与卷积网络相比,基于 Transformer 的架构可以在基准分类任务上取得有竞争力的结果。然而,注意力算子的计算复杂性意味着...
与DETR和可变形DETR范式不同,本文将ViT与RPN进行结合,即将CNN主干替换为transformer,组成为:ViT-FRCNN,作者称这可视为迈向复杂视觉任务(例如目标检测)纯transformer解决方案的重要基石。 注:文末附【Transformer】和【目标检测】学习交流群 Toward Transformer-Based Object Detection 作者单位:Pintere... 查看原文 DETR...
具体而言,保持图2中的总体框架不变,并使用Swin transformer骨干作为联合COD和COL模块的骨干。三个任务的性能分别显示为“STCOD”、“STCOL”和“STCOR”。与使用ResNet50骨干网(“PTCOD”和“PTCOL”)相比,使用Swin transformer骨干网的COD和COL任务的性能显著更好,这验证了transformer骨干网在COD和COL方面的优势。
The Robotic View Transformer for 3D Object Manipulation is a transformer-based architecture that uses an attention mechanism to aggregate information across different views of an object, re-rendering the camera input from virtual views around the robot workspace. Understanding time to AI impact Until ...
By integrating wavelet transforms with CNN-Transformer modules and generative adversarial networks, WECT enhances image quality and outperforms state-of-the-art methods in both quantitative and qualitative analyses. Muhammad Ahmad et al. [25] proposed WaveFormer, a novel transformer-based approach for...
While the early approaches relied heavily on handcrafted features and rule-based systems, advances in deep learning and transformer models have driven substantial improvements. Classic knowledge extraction systems, such as the Mayo clinical text analysis and knowledge extraction system (cTAKES) [11], ...
In addition to manual interpretation, bio-inspired computational intelligence methods (e.g., convolutional neural networks and vision transformer) have markedly boosted machine performances in remote sensing image (RSI) processing (Aleissaee et al.,2023; Zhong et al.,2018). These bio-inspired method...
transformertoken blurringVISIONAlthough self-supervised depth estimation models based on transformers have achieved success, lightweight depth prediction networks exhibit a particularly pronounced issue with depth prediction blurriness at object boundaries compared to standard depth prediction net...
PointNet++, DGCNN, PointCNN, PointMLP, CurveNet, Stratified Transformer (ST)37, PointMamba, and DeLA. For instance segmentation, the current state-of-the-art models on the S3DIS dataset, Mask3D38and OneFormer3D39, were chosen. Detailed testing and evaluation were conducted on the Crops3D dat...
Z. Liu, Y. T. Lin, Y. Cao, H. Hu, Y. X. Wei, Z. Zhang, S. Lin, B. N. Guo. Swin transformer: Hierarchical vision transformer using shifted windows. InProceedings of IEEE/CVF International Conference on Computer Vision, IEEE, Montreal, Canada, pp. 9992–10002, 2021. DOI:https:/...