17 citations · 24 across the 6 of their papers we have counts for
9 papers
SceneComposer: Any-Level Semantic Image Synthesis
Yu Zeng, Zhe Lin, Jianming Zhang +4
We propose a new framework for conditional image synthesis from semantic layouts of any precision levels, ranging from pure text to a 2D semantic canvas with precise shapes. More s…
Improving the Reliability for Confidence Estimation
Haoxuan Qu, Yanchao Li, Lin Geng Foo +3
Confidence estimation, a task that aims to evaluate the trustworthiness of the model's prediction output during deployment, has received lots of research attention recently, due to…
Unified Pretraining Framework for Document Understanding
Jiuxiang Gu, Jason Kuen, Vlad I. Morariu +5
Document intelligence automates the extraction of information from documents and supports many business applications. Recent self-supervised learning methods on large-scale unlabel…
GALA: Toward Geometry-and-Lighting-Aware Object Search for Compositing
Sijie Zhu, Zhe Lin, Scott Cohen +3
Compositing-aware object search aims to find the most compatible objects for compositing given a background image and a query bounding box. Previous works focus on learning compati…
Multi-Scale Aligned Distillation for Low-Resolution Detection
Lu Qi, Jason Kuen, Jiuxiang Gu +5
In instance-level detection tasks (e.g., object detection), reducing input resolution is an easy option to improve runtime efficiency. However, this option traditionally hurts the…
SelfDoc: Self-Supervised Document Representation Learning
Peizhao Li, Jiuxiang Gu, Jason Kuen +5
We propose SelfDoc, a task-agnostic pre-training framework for document image understanding. Because documents are multimodal and are intended for sequential reading, our framework…