22 citations · 52 across the 11 of their papers we have counts for
11 papers
TurboEdit: Instant text-based image editing
Zongze Wu, Nicholas Kolkin, Jonathan Brandt +2
We address the challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion t…
StreamHover: Livestream Transcript Summarization and Annotation
Sangwoo Cho, Franck Dernoncourt, Tim Ganter +7
With the explosive growth of livestream broadcasting, there is an urgent need for new summarization technology that enables us to create a preview of streamed content and tap into…
LPaintB: Learning to Paint from Self-Supervision
Biao Jia, Jonathan Brandt, Radomir Mech +2
We present a novel reinforcement learning-based natural media painting algorithm. Our goal is to reproduce a reference image using brush strokes and we encode the objective through…
PaintBot: A Reinforcement Learning Approach for Natural Media Painting
Biao Jia, Chen Fang, Jonathan Brandt +2
We propose a new automated digital painting framework, based on a painting agent trained through reinforcement learning. To synthesize an image, the agent selects a sequence of con…
Hotels-50K: A Global Hotel Recognition Dataset
Abby Stylianou, Hong Xuan, Maya Shende +3
Recognizing a hotel from an image of a hotel room is important for human trafficking investigations. Images directly link victims to places and can help verify where victims have b…
Learning to Sketch with Deep Q Networks and Demonstrated Strokes
Tao Zhou, Chen Fang, Zhaowen Wang +5
Doodling is a useful and common intelligent skill that people can learn and master. In this work, we propose a two-stage learning framework to teach a machine to doodle in a simula…
Top-down Neural Attention by Excitation Backprop
Jianming Zhang, Zhe Lin, Jonathan Brandt +2
We aim to model the top-down attention of a Convolutional Neural Network (CNN) classifier for generating task-specific attention maps. Inspired by a top-down human visual attention…
DeepFont: Identify Your Font from An Image
Zhangyang Wang, Jianchao Yang, Hailin Jin +4
As font is one of the core design concepts, automatic font identification and similar font suggestion from an image or photo has been on the wish list of many designers. We study t…
Real-World Font Recognition Using Deep Network and Domain Adaptation
Zhangyang Wang, Jianchao Yang, Hailin Jin +4
We address a challenging fine-grain classification problem: recognizing a font style from an image of text. In this task, it is very easy to generate lots of rendered font examples…
Decomposition-Based Domain Adaptation for Real-World Font Recognition
Zhangyang Wang, Jianchao Yang, Hailin Jin +4
We present a domain adaption framework to address a domain mismatch between synthetic training and real-world testing data. We demonstrate our method on a challenging fine-grain cl…
Scalable Similarity Learning using Large Margin Neighborhood Embedding
Zhaowen Wang, Jianchao Yang, Zhe Lin +3
Classifying large-scale image data into object categories is an important problem that has received increasing research attention. Given the huge amount of data, non-parametric app…