Articoli con mandati relativi all'accesso pubblico - David ForsythUlteriori informazioni
Non disponibile pubblicamente: 1
POVNet: Image-based virtual try-on through accurate warping and residual
K Li, J Zhang, D Forsyth
IEEE transactions on pattern analysis and machine intelligence 45 (10 …, 2023
Mandati: US National Science Foundation, US Department of Defense
Disponibili pubblicamente: 21
Safetynet: Detecting and rejecting adversarial examples robustly
J Lu, T Issaranon, D Forsyth
Proceedings of the IEEE international conference on computer vision, 446-454, 2017
Mandati: US National Science Foundation, US Department of Defense
Learning type-aware embeddings for fashion compatibility
MI Vasileva, BA Plummer, K Dusad, S Rajpal, R Kumar, D Forsyth
Proceedings of the European conference on computer vision (ECCV), 390-405, 2018
Mandati: US National Science Foundation, US Department of Defense
Learning diverse image colorization
A Deshpande, J Lu, MC Yeh, M Jin Chong, D Forsyth
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Mandati: US National Science Foundation, US Department of Defense
Max-sliced wasserstein distance and its use for gans
I Deshpande, YT Hu, R Sun, A Pyrros, N Siddiqui, S Koyejo, Z Zhao, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
Mandati: US National Science Foundation
Fast, diverse and accurate image captioning guided by part-of-speech
A Deshpande, J Aneja, L Wang, AG Schwing, D Forsyth
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
Mandati: US National Science Foundation, US Department of Defense
Structural consistency and controllability for diverse colorization
S Messaoud, D Forsyth, AG Schwing
Proceedings of the European Conference on Computer Vision (ECCV), 596-612, 2018
Mandati: US National Science Foundation
Retrieve in style: Unsupervised facial feature transfer and retrieval
MJ Chong, WS Chu, A Kumar, D Forsyth
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Mandati: US National Science Foundation, US Department of Defense
How to steer your adversary: Targeted and efficient model stealing defenses with gradient redirection
M Mazeika, B Li, D Forsyth
International conference on machine learning, 15241-15254, 2022
Mandati: US National Science Foundation
Polarization-based underwater geolocalization with deep learning
X Bai, Z Liang, Z Zhu, A Schwing, D Forsyth, V Gruev
eLight 3 (1), 15, 2023
Mandati: US Department of Defense
Climatenerf: Extreme weather synthesis in neural radiance field
Y Li, ZH Lin, D Forsyth, JB Huang, S Wang
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
Mandati: US National Science Foundation
Why do these match? explaining the behavior of image similarity models
BA Plummer, MI Vasileva, V Petsiuk, K Saenko, D Forsyth
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Mandati: US National Science Foundation, US Department of Defense
Intrinsic image decomposition using paradigms
D Forsyth, JJ Rock
IEEE transactions on pattern analysis and machine intelligence 44 (11), 7624 …, 2021
Mandati: US National Science Foundation, US Department of Defense
Cut-and-paste object insertion by enabling deep image prior for reshading
A Bhattad, DA Forsyth
2022 International Conference on 3D Vision (3DV), 332-341, 2022
Mandati: US National Science Foundation
An approximate shading model with detail decomposition for object relighting
Z Liao, K Karsch, H Zhang, D Forsyth
International Journal of Computer Vision 127, 22-37, 2019
Mandati: US National Science Foundation, US Department of Defense, National Natural …
Lsd-structurenet: Modeling levels of structural detail in 3d part hierarchies
D Roberts, A Danielyan, H Chu, M Golparvar-Fard, D Forsyth
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Mandati: US National Science Foundation
Convex decomposition of indoor scenes
V Vavilala, D Forsyth
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
Mandati: US National Science Foundation
Sim-on-Wheels: Physical World in the Loop Simulation for Self-Driving
Y Shen, B Chandaka, ZH Lin, A Zhai, H Cui, D Forsyth, S Wang
IEEE Robotics and Automation Letters, 2023
Mandati: US National Science Foundation
Angle of polarization calibration for omnidirectional polarization cameras
X Bai, Z Zhu, A Schwing, D Forsyth, V Gruev
Optics Express 31 (4), 6759-6769, 2023
Mandati: US Department of Defense
Counterfactual depth from a single rgb image
T Issaranon, C Zou, D Forsyth
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Mandati: US Department of Defense
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