50 citations · 73 across the 27 of their papers we have counts for
27 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…
ToSA: Token Selective Attention for Efficient Vision Transformers
Manish Kumar Singh, Rajeev Yasarla, Hong Cai +2
In this paper, we propose a novel token selective attention approach, ToSA, which can identify tokens that need to be attended as well as those that can skip a transformer layer. M…
FouRA: Fourier Low Rank Adaptation
Shubhankar Borse, Shreya Kadambi, Nilesh Prasad Pandey +7
While Low-Rank Adaptation (LoRA) has proven beneficial for efficiently fine-tuning large models, LoRA fine-tuned text-to-image diffusion models lack diversity in the generated imag…
Segmentation-Free Guidance for Text-to-Image Diffusion Models
Kambiz Azarian, Debasmit Das, Qiqi Hou +1
We introduce segmentation-free guidance, a novel method designed for text-to-image diffusion models like Stable Diffusion. Our method does not require retraining of the diffusion m…
EdgeRelight360: Text-Conditioned 360-Degree HDR Image Generation for Real-Time On-Device Video Portrait Relighting
Min-Hui Lin, Mahesh Reddy, Guillaume Berger +3
In this paper, we present EdgeRelight360, an approach for real-time video portrait relighting on mobile devices, utilizing text-conditioned generation of 360-degree high dynamic ra…
SciFlow: Empowering Lightweight Optical Flow Models with Self-Cleaning Iterations
Jamie Menjay Lin, Jisoo Jeong, Hong Cai +3
Optical flow estimation is crucial to a variety of vision tasks. Despite substantial recent advancements, achieving real-time on-device optical flow estimation remains a complex ch…