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20152024
most citedYou Only Need Adversarial Supervision for Semantic Image Synthesis

70 citations · 231 across the 35 of their papers we have counts for

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Showing 2020Show all

12 papers · 1 filter

cs.CV202070 cited

You Only Need Adversarial Supervision for Semantic Image Synthesis

Vadim Sushko, Edgar Schönfeld, Dan Zhang +3

Despite their recent successes, GAN models for semantic image synthesis still suffer from poor image quality when trained with only adversarial supervision. Historically, additiona…

cs.CV2020

PoseTrackReID: Dataset Description

Andreas Doering, Di Chen, Shanshan Zhang +2

Current datasets for video-based person re-identification (re-ID) do not include structural knowledge in form of human pose annotations for the persons of interest. Nonetheless, po…

cs.CV2020

Haar Wavelet based Block Autoregressive Flows for Trajectories

Apratim Bhattacharyya, Christoph-Nikolas Straehle, Mario Fritz +1

Prediction of trajectories such as that of pedestrians is crucial to the performance of autonomous agents. While previous works have leveraged conditional generative models like GA…

cs.CV2020

Synthetic Convolutional Features for Improved Semantic Segmentation

Yang He, Bernt Schiele, Mario Fritz

Recently, learning-based image synthesis has enabled to generate high-resolution images, either applying popular adversarial training or a powerful perceptual loss. However, it rem…

cs.CV2020

Long-Term Anticipation of Activities with Cycle Consistency

Yazan Abu Farha, Qiuhong Ke, Bernt Schiele +1

With the success of deep learning methods in analyzing activities in videos, more attention has recently been focused towards anticipating future activities. However, most of the w…

cs.CV2020

Kinematic 3D Object Detection in Monocular Video

Garrick Brazil, Gerard Pons-Moll, Xiaoming Liu +1

Perceiving the physical world in 3D is fundamental for self-driving applications. Although temporal motion is an invaluable resource to human vision for detection, tracking, and de…