9 citations · 10 across the 6 of their papers we have counts for
6 papers
Open Vocabulary Panoptic Segmentation With Retrieval Augmentation
Nafis Sadeq, Qingfeng Liu, Mostafa El-Khamy
Given an input image and set of class names, panoptic segmentation aims to label each pixel in an image with class labels and instance labels. In comparison, Open Vocabulary Panopt…
Hardware-Friendly Static Quantization Method for Video Diffusion Transformers
Sanghyun Yi, Qingfeng Liu, Mostafa El-Khamy
Diffusion Transformers for video generation have gained significant research interest since the impressive performance of SORA. Efficient deployment of such generative-AI models on…
HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM Prompts
Xinyu Liu, Yingqing He, Lanqing Guo +10
The potential for higher-resolution image generation using pretrained diffusion models is immense, yet these models often struggle with issues of object repetition and structural a…
1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation
Qingfeng Liu, Mostafa El-Khamy, Kee-Bong Song
The third Pixel-level Video Understanding in the Wild (PVUW CVPR 2024) challenge aims to advance the state of art in video understanding through benchmarking Video Panoptic Segment…
SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models
Sara Babakniya, Ahmed Roushdy Elkordy, Yahya H. Ezzeldin +4
Transfer learning via fine-tuning pre-trained transformer models has gained significant success in delivering state-of-the-art results across various NLP tasks. In the absence of c…
GSANet: Semantic Segmentation with Global and Selective Attention
Qingfeng Liu, Mostafa El-Khamy, Dongwoon Bai +1
This paper proposes a novel deep learning architecture for semantic segmentation. The proposed Global and Selective Attention Network (GSANet) features Atrous Spatial Pyramid Pooli…