As a work exploring the existing trade-off between accuracy and efficiency in the context of point cloud processing, Point Transformer V3 (PTV3) has made significant advancements in computational ...

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...

This project implements Vision Transformer (ViT) for image classification. Unlike CNNs, ViT splits images into patches and processes them as sequences using transformer architecture. It includes patch ...

Abstract: Transformer architecture has enabled recent progress in speech enhancement. Since Transformers are position-agostic, positional encoding is the de facto standard component used to enable ...

Rotary Positional Embedding (RoPE) is a widely used technique in Transformers, influenced by the hyperparameter theta (θ). However, the impact of varying *fixed* theta values, especially the trade-off ...

Abstract: Recently, the Vision Transformer (ViT) has achieved outstanding performance in various computer vision tasks. Positional encoding is an indispensable component of ViT for handling the ...

The attention mechanism is a core primitive in modern large language models (LLMs) and AI more broadly. Since attention by itself is permutation-invariant, position encoding is essential for modeling ...

self.temperature = nn.Parameter(torch.ones(num_heads, 1, 1)) self.qkv = nn.Conv2d(dim, dim * 3, kernel_size=1, bias=bias) # 1*1 维度升3倍, 均分成q,k,v self.qkv ...