4 citations · 4 across the 5 of their papers we have counts for
5 papers
PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer
Pierre-David Letourneau, Manish Kumar Singh, Hsin-Pai Cheng +6
We present Polynomial Attention Drop-in Replacement (PADRe), a novel and unifying framework designed to replace the conventional self-attention mechanism in transformer models. Not…
Enhancing Retrieval and Managing Retrieval: A Four-Module Synergy for Improved Quality and Efficiency in RAG Systems
Yunxiao Shi, Xing Zi, Zijing Shi +3
Retrieval-augmented generation (RAG) techniques leverage the in-context learning capabilities of large language models (LLMs) to produce more accurate and relevant responses. Origi…
Parameter Hierarchical Optimization for Visible-Infrared Person Re-Identification
Zeng YU, Yunxiao Shi
Visible-infrared person re-identification (VI-reID) aims at matching cross-modality pedestrian images captured by disjoint visible or infrared cameras. Existing methods alleviate t…
DeCoTR: Enhancing Depth Completion with 2D and 3D Attentions
Yunxiao Shi, Manish Kumar Singh, Hong Cai +1
In this paper, we introduce a novel approach that harnesses both 2D and 3D attentions to enable highly accurate depth completion without requiring iterative spatial propagations. S…
EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation
Yunxiao Shi, Hong Cai, Amin Ansari +1
The ubiquitous multi-camera setup on modern autonomous vehicles provides an opportunity to construct surround-view depth. Existing methods, however, either perform independent mono…