ICRA 2019 We show that object-centric models outperform object-agnostic methods in scenes with other vehicles and pedestrians.
ECCV 2018 We introduce SkipNet, a modified residual network, that uses a gating network to selectively skip convolutional blocks based on the activations of the previous layer.
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
ECCV 2018 We aim to characterize adversarial examples based on spatial context information in semantic segmentation.
UAI 2018 We introduce the “I Don’t Know” (IDK) prediction cascades framework to accelerate inference without a loss in prediction accuracy.
CVPR 2018 Oral We augment standard architectures with deeper aggregation to better fuse information across layers.
CVPR 2018 Spotlight We develop a local texture loss in addition to adversarial and content loss to train the generative network.
CVPR 2018 We introduce an automatic method for editing a portrait photo so that the subject appears to be wearing makeup in the style of another person in a reference photo.
3DV 2017 We propose using a generative adversarial network (GAN) to assist a novice user in designing real-world shapes with a simple interface.
CVPR 2017 We show that dilated residual networks (DRNs) outperform their non-dilated counterparts in image classification without increasing the model’s depth or complexity.