activity
20182022
most citedEfficient Project Gradient Descent for Ensemble Adversarial Attack

4 citations · 9 across the 3 of their papers we have counts for

collaborators

7 papers

cs.AI20222 cited

Co-design of Embodied Neural Intelligence via Constrained Evolution

Zhiquan Wang, Bedrich Benes, Ahmed H. Qureshi +1

We introduce a novel co-design method for autonomous moving agents' shape attributes and locomotion by combining deep reinforcement learning and evolution with user control. Our ma…

cs.GR2020

Procedural Urban Forestry

Till Niese, Sören Pirk, Matthias Albrecht +2

The placement of vegetation plays a central role in the realism of virtual scenes. We introduce procedural placement models (PPMs) for vegetation in urban layouts. PPMs are environ…

cs.CV2020

SSN: Soft Shadow Network for Image Compositing

Yichen Sheng, Jianming Zhang, Bedrich Benes

We introduce an interactive Soft Shadow Network (SSN) to generates controllable soft shadows for image compositing. SSN takes a 2D object mask as input and thus is agnostic to imag…

cs.RO20193 cited

LeRoP: A Learning-Based Modular Robot Photography Framework

Hao Kang, Jianming Zhang, Haoxiang Li +3

We introduce a novel framework for automatic capturing of human portraits. The framework allows the robot to follow a person to the desired location using a Person Re-identificatio…

cs.GR2019

PTRM: Perceived Terrain Realism Metrics

Suren Deepak Rajasekaran, Hao Kang, Bedrich Benes +5

Terrains are visually important and commonly used in computer graphics. While many algorithms for their generation exist, it is difficult to assess the realism of a generated terra…

cs.LG20194 cited

Efficient Project Gradient Descent for Ensemble Adversarial Attack

Fanyou Wu, Rado Gazo, Eva Haviarova +1

Recent advances show that deep neural networks are not robust to deliberately crafted adversarial examples which many are generated by adding human imperceptible perturbation to cl…