Search Results for author:
Found 8 papers, 7 papers with code
WAIT: Feature Warping for Animation to Illustration video Translation using GANs
Current state-of-the-art video-to-video translation models rely on having a video sequence or a single style image to stylize an input video.
Improving Sketch Colorization using Adversarial Segmentation Consistency
We leverage semantic image segmentation from a general-purpose panoptic segmentation network to generate an additional adversarial loss function.
HoughNet: Integrating near and long-range evidence for visual detection
This paper presents HoughNet, a one-stage, anchor-free, voting-based, bottom-up object detection method.
Adversarial Segmentation Loss for Sketch Colorization
Our loss function can be integrated to any baseline GAN model.
Reducing Label Noise in Anchor-Free Object Detection
In this paper, we propose a new labeling strategy aimed to reduce the label noise in anchor-free detectors.
Ranked #111 on
Object Detection
on COCO test-dev
HoughNet: Integrating near and long-range evidence for bottom-up object detection
We further validate the effectiveness of our proposal in another task, namely, "labels to photo" image generation by integrating the voting module of HoughNet to two different GAN models and showing that the accuracy is significantly improved in both cases.
Ranked #101 on
Object Detection
on COCO minival
GANILLA: Generative Adversarial Networks for Image to Illustration Translation
To address this problem, we propose a new framework for the quantitative evaluation of image-to-illustration models, where both content and style are taken into account using separate classifiers.
DRAW: Deep networks for Recognizing styles of Artists Who illustrate children's books
The style was noticeable in other characters of the same illustrator in different books as well.
