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Noshaba Cheema
Person information
- affiliation: Max Planck Institute for Informatics, Saarbrücken, Germany
- affiliation: German Research Centre for Artificial Intelligence (DFKI), Saarbrücken, Germany
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2020 – today
- 2023
- [c14]Aakash Rajpal, Noshaba Cheema, Klaus Illgner-Fehns, Philipp Slusallek, Sunil Prasad Jaiswal:
High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation. CVPR Workshops 2023: 1188-1198 - [c13]Mehran Jeelani, Sadbhawna, Noshaba Cheema, Klaus Illgner-Fehns, Philipp Slusallek, Sunil Prasad Jaiswal:
Expanding Synthetic Real-World Degradations for Blind Video Super Resolution. CVPR Workshops 2023: 1199-1208 - [c12]Noshaba Cheema
, Rui Xu
Discovering Fatigued Movements for Virtual Character Animation. SIGGRAPH Asia 2023: 47:1-47:12 - [i7]Aakash Rajpal, Noshaba Cheema, Klaus Illgner-Fehns, Philipp Slusallek, Sunil Prasad Jaiswal:
High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation. CoRR abs/2305.01732 (2023) - [i6]Elena Kosheleva, Sunil Prasad Jaiswal, Faranak Shamsafar, Noshaba Cheema, Klaus Illgner-Fehns, Philipp Slusallek:
Edge-aware Consistent Stereo Video Depth Estimation. CoRR abs/2305.02645 (2023) - [i5]Mehran Jeelani, Sadbhawna, Noshaba Cheema, Klaus Illgner-Fehns, Philipp Slusallek, Sunil Prasad Jaiswal:
Expanding Synthetic Real-World Degradations for Blind Video Super Resolution. CoRR abs/2305.02660 (2023) - [i4]Noshaba Cheema, Rui Xu, Nam Hee Kim, Perttu Hämäläinen, Vladislav Golyanik, Marc Habermann, Christian Theobalt, Philipp Slusallek:
Discovering Fatigued Movements for Virtual Character Animation. CoRR abs/2310.08583 (2023) - 2021
- [c11]Samim Zahoor Taray, Sunil Prasad Jaiswal, Shivam Sharma, Noshaba Cheema, Klaus Illgner-Fehns, Philipp Slusallek, Ivo Ihrke:
A Comparative Study of PnP and Learning Approaches to Super-Resolution in a Real-World Setting. GCPR 2021: 313-327 - [c10]Anindita Ghosh
Synthesis of Compositional Animations from Textual Descriptions. ICCV 2021: 1376-1386 - [c9]Anindita Ghosh, Noshaba Cheema, Cennet Oguz, Christian Theobalt
Text-Based Motion Synthesis with a Hierarchical Two-Stream RNN. SIGGRAPH Posters 2021: 42:1-42:2 - [c8]Kenny Mitchell, Babis Koniaris, Monica Tamariz
Embodied online dance learning objectives of CAROUSEL+. VR Workshops 2021: 309-313 - [i3]Anindita Ghosh, Noshaba Cheema, Cennet Oguz, Christian Theobalt, Philipp Slusallek:
Synthesis of Compositional Animations from Textual Descriptions. CoRR abs/2103.14675 (2021) - 2020
- [c7]Noshaba Cheema
Predicting Mid-Air Interaction Movements and Fatigue Using Deep Reinforcement Learning. CHI 2020: 1-13
2010 – 2019
- 2019
- [c6]Erik Herrmann, Han Du, André Antakli, Dmitri Rubinstein, René Schubotz
Motion Data and Model Management for Applied Statistical Motion Synthesis. STAG 2019: 79-88 - [c5]Han Du
Stylistic Locomotion Modeling with Conditional Variational Autoencoder. Eurographics (Short Papers) 2019: 9-12 - [c4]Noshaba Cheema
Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks. Eurographics (Short Papers) 2019: 69-72 - [c3]Janis Sprenger, Han Du, Noshaba Cheema
Learning a Continuous Control of Motion Style from Natural Examples. MIG 2019: 31:1-31:10 - [c2]Erik Herrmann, Han Du, Noshaba Cheema
Adaptive gaussian mixture trajectory model for physical model control using motion capture data. I3D 2019: 12:1-12:8 - [i2]Noshaba Cheema
Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks. CoRR abs/1903.00695 (2019) - 2018
- [c1]Noshaba Cheema
Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data. Symposium on Computer Animation (Posters) 2018: 5-6 - [i1]Noshaba Cheema, Somayeh Hosseini, Janis Sprenger, Erik Herrmann, Han Du, Klaus Fischer, Philipp Slusallek:
Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data. CoRR abs/1806.09174 (2018)
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