164 citations · 424 across the 13 of their papers we have counts for
13 papers
LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models
Long Lian, Boyi Li, Adam Yala +1
Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex…
Re-evaluating the Need for Multimodal Signals in Unsupervised Grammar Induction
Boyi Li, Rodolfo Corona, Karttikeya Mangalam +7
Are multimodal inputs necessary for grammar induction? Recent work has shown that multimodal training inputs can improve grammar induction. However, these improvements are based on…
WiCV 2021: The Eighth Women In Computer Vision Workshop
Arushi Goel, Niveditha Kalavakonda, Nour Karessli +5
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2021, organized alongside the virtual CVPR 2021. It provides a voice to a minority (female) group…
Language-driven Semantic Segmentation
Boyi Li, Kilian Q. Weinberger, Serge Belongie +2
We present LSeg, a novel model for language-driven semantic image segmentation. LSeg uses a text encoder to compute embeddings of descriptive input labels (e.g., "grass" or "buildi…
SITTA: Single Image Texture Translation for Data Augmentation
Boyi Li, Yin Cui, Tsung-Yi Lin +1
Recent advances in data augmentation enable one to translate images by learning the mapping between a source domain and a target domain. Existing methods tend to learn the distribu…
WiCV 2020: The Seventh Women In Computer Vision Workshop
Hazel Doughty, Nour Karessli, Kathryn Leonard +5
In this paper we present the details of Women in Computer Vision Workshop - WiCV 2020, organized in alongside virtual CVPR 2020. This event aims at encouraging the women researcher…
On Feature Normalization and Data Augmentation
Boyi Li, Felix Wu, Ser-Nam Lim +2
The moments (a.k.a., mean and standard deviation) of latent features are often removed as noise when training image recognition models, to increase stability and reduce training ti…
Integrated Triaging for Fast Reading Comprehension
Felix Wu, Boyi Li, Lequn Wang +3
Although according to several benchmarks automatic machine reading comprehension (MRC) systems have recently reached super-human performance, less attention has been paid to their…
Positional Normalization
Boyi Li, Felix Wu, Kilian Q. Weinberger +1
A popular method to reduce the training time of deep neural networks is to normalize activations at each layer. Although various normalization schemes have been proposed, they all…
FastFusionNet: New State-of-the-Art for DAWNBench SQuAD
Felix Wu, Boyi Li, Lequn Wang +3
In this technical report, we introduce FastFusionNet, an efficient variant of FusionNet [12]. FusionNet is a high performing reading comprehension architecture, which was designed…
Benchmarking Single Image Dehazing and Beyond
Boyi Li, Wenqi Ren, Dengpan Fu +4
We present a comprehensive study and evaluation of existing single image dehazing algorithms, using a new large-scale benchmark consisting of both synthetic and real-world hazy ima…
End-to-End United Video Dehazing and Detection
Boyi Li, Xiulian Peng, Zhangyang Wang +2
The recent development of CNN-based image dehazing has revealed the effectiveness of end-to-end modeling. However, extending the idea to end-to-end video dehazing has not been expl…
An All-in-One Network for Dehazing and Beyond
Boyi Li, Xiulian Peng, Zhangyang Wang +2
This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net). It is designed based on a re-formulated a…