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Zoltán Ádám Milacski
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2020 – today
- 2025
- [c15]Zoltán Ádám Milacski, Koichiro Niinuma, Ryosuke Kawamura, Fernando De la Torre, László A. Jeni:
GHOST: Grounded Human Motion Generation with Open Vocabulary Scene-and-Text Contexts. WACV 2025: 4108-4118 - 2024
- [c14]Heng Yu, Joel Julin, Zoltán Ádám Milacski, Koichiro Niinuma, László A. Jeni:
CoGS: Controllable Gaussian Splatting. CVPR 2024: 21624-21633 - [c13]José Ribeiro-Gomes, Tianhui Cai, Zoltán Ádám Milacski, Chen Wu, Aayush Prakash, Shingo Takagi, Amaury Aubel, Daeil Kim, Alexandre Bernardino, Fernando De la Torre:
MotionGPT: Human Motion Synthesis with Improved Diversity and Realism via GPT-3 Prompting. WACV 2024: 5058-5068 - [i8]Zoltan A. Milacski, Koichiro Niinuma, Ryosuke Kawamura, Fernando De la Torre, László A. Jeni:
GHOST: Grounded Human Motion Generation with Open Vocabulary Scene-and-Text Contexts. CoRR abs/2405.18438 (2024) - 2023
- [c12]Heng Yu, Zoltan A. Milacski, László A. Jeni:
Unsupervised Style-based Explicit 3D Face Reconstruction from Single Image. CVPR Workshops 2023: 719-729 - [c11]Heng Yu, Joel Julin, Zoltan A. Milacski, Koichiro Niinuma, László A. Jeni:
DyLiN: Making Light Field Networks Dynamic. CVPR 2023: 12397-12406 - [i7]Heng Yu, Joel Julin, Zoltan A. Milacski, Koichiro Niinuma, László A. Jeni:
DyLiN: Making Light Field Networks Dynamic. CoRR abs/2303.14243 (2023) - [i6]Heng Yu, Zoltan A. Milacski, László A. Jeni:
Unsupervised Style-based Explicit 3D Face Reconstruction from Single Image. CoRR abs/2304.12455 (2023) - [i5]Heng Yu, Joel Julin, Zoltán Ádám Milacski, Koichiro Niinuma, László A. Jeni:
CoGS: Controllable Gaussian Splatting. CoRR abs/2312.05664 (2023) - 2022
- [c10]Dávid Szeghy, Mahmoud Aslan
, Áron Fóthi, Balázs Mészáros, Zoltán Ádám Milacski, András Lorincz:
Structural Extensions of Basis Pursuit: Guarantees on Adversarial Robustness. DeLTA 2022: 77-85 - [i4]Dávid Szeghy, Mahmoud Aslan, Áron Fóthi, Balázs Mészáros
Structural Extensions of Basis Pursuit: Guarantees on Adversarial Robustness. CoRR abs/2205.08955 (2022) - 2021
- [b1]Zoltán Ádám Milacski:
Temporal Reconstruction Methods in Self-Supervised Machine Learning. Eötvös Loránd University, Hungary, 2021 - [j3]Ádám Fodor
Speech De-identification with Deep Neural Networks. Acta Cybern. 25(2): 257-269 (2021) - [j2]Changhee Han
MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction. BMC Bioinform. 22-S(2): 31 (2021) - 2020
- [c9]Zoltán Ádám Milacski, Barnabás Póczos, András Lörincz:
VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing. ICML 2020: 6893-6904 - [c8]Áron Fóthi, Kinga Bettina Faragó, László Kopácsi, Zoltán Ádám Milacski, Viktor Varga, András Lorincz:
Multi Object Tracking for Similar Instances: A Hybrid Architecture. ICONIP (1) 2020: 436-447 - [i3]Changhee Han, Leonardo Rundo, Kohei Murao, Tomoyuki Noguchi, Yuki Shimahara, Zoltán Ádám Milacski, Saori Koshino, Evis Sala, Hideki Nakayama, Shin'ichi Satoh:
MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction. CoRR abs/2007.13559 (2020)
2010 – 2019
- 2019
- [c7]Zoltán Ádám Milacski, Barnabás Póczos, András Lorincz:
Differentiable Unrolled Alternating Direction Method of Multipliers for OneNet. BMVC 2019: 140 - [c6]Changhee Han, Leonardo Rundo
GAN-Based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis. CIBB 2019: 44-54 - [c5]Zoltán Ádám Milacski, Barnabás Póczos, András Lörincz:
Group k-Sparse Temporal Convolutional Neural Networks: Unsupervised Pretraining for Video Classification. IJCNN 2019: 1-10 - [i2]Changhee Han, Leonardo Rundo, Kohei Murao, Zoltán Ádám Milacski, Kazuki Umemoto, Hideki Nakayama, Shin'ichi Satoh:
GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis. CoRR abs/1906.06114 (2019) - 2018
- [j1]András Lörincz, Máté Csákvári, Áron Fóthi, Zoltán Ádám Milacski
Towards reasoning based representations: Deep Consistence Seeking Machine. Cogn. Syst. Res. 47: 92-108 (2018) - 2016
- [c4]András Lörincz
Estimating Cartesian Compression via Deep Learning. AGI 2016: 294-304 - [i1]András Lörincz, Máté Csákvári, Áron Fóthi, Zoltán Ádám Milacski, András Sárkány, Zoltán Tosér:
Cognitive Deep Machine Can Train Itself. CoRR abs/1612.00745 (2016) - 2015
- [c3]Kinga Bettina Faragó, Zoltán Ádám Milacski, András Németh, András Lörincz:
Enhancing Crowdsourced Applications via Incorporated Practice Sessions. GamifIR@ECIR 2015: 41-43 - [c2]Zoltán Ádám Milacski
Robust Detection of Anomalies via Sparse Methods. ICONIP (3) 2015: 419-426 - [c1]Andras Mihaly, Zoltán Ádám Milacski
Cost and risk sensitive decision making and control for highway overtaking maneuver. MT-ITS 2015: 87-92
Coauthor Index
aka: András Lorincz
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last updated on 2025-04-24 21:07 CEST by the dblp team
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