Search Results for author:
Found 6 papers, 2 papers with code
Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards
The goal of this work is to develop a novel learning framework for accurate and expressive fashion captioning.
Learning Color Compatibility in Fashion Outfits
Color compatibility is important for evaluating the compatibility of a fashion outfit, yet it was neglected in previous studies.
Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation
In this paper, we present new data pre-processing and augmentation techniques for DNN-based raw image denoising.
GeoNet: Deep Geodesic Networks for Point Cloud Analysis
Surface-based geodesic topology provides strong cues for object semantic analysis and geometric modeling.
A Taught-Obesrve-Ask (TOA) Method for Object Detection with Critical Supervision
Being inspired by child's learning experience - taught first and followed by observation and questioning, we investigate a critically supervised learning methodology for object detection in this work.
Semantic Segmentation with Reverse Attention
Recent development in fully convolutional neural network enables efficient end-to-end learning of semantic segmentation.
Ranked #107 on
Semantic Segmentation
on NYU Depth v2
