Monday 10/11 |
Tuesday 10/12 |
Wednesday 10/13 |
Thursday 10/14 |
Friday 10/15 |
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Self-Supervised Object Detection via Generative Image Synthesis | Session 7A | 8:00–9:00 a.m. EDT |
Video Matting via Consistency-Regularized Graph Neural Networks | Session 4B | 8:00–9:00 a.m. EDT |
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Active Learning for Deep Object Detection via Probabilistic Modeling | Session 8A | 9:00–10:00 a.m. EDT |
Deep Permutation Equivariant Structure from Motion | Session 5B | 9:00–10:00 a.m. EDT |
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Video Autoencoder: Self-Supervised Disentanglement of 3D Structure and Motion | Session 8A | 9:00–10:00 a.m. EDT |
Self-Calibrating Neural Radiance Field | Session 5B | 9:00–10:00 a.m. EDT |
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Physics-Based Human Motion Estimation and Synthesis from Videos | Session 9A | 10:00–11:00 a.m. EDT |
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Learning Indoor Reverse Rendering with 3D Spatially Varying Lighting | Session 10B | 10:00–11:00 a.m. EDT |
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3DStyleNet: Creating 3D Shapes with Geometrics and Texture Style Variations | Session 10B | 10:00–11:00 a.m. EDT |
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GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds | Session 11B | 11:00 a.m.–12:00 p.m. EDT |
Differentiable 3D Vision and Graphics | Half day, afternoon | Workshop |
T-AutoML: Automated Machine Learning for Lesion Segmentation Using Transformers in 3D Medical Imaging | Session 3A | 12:00–1:00 p.m. EDT |
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The Second Learning for Computational Imaging (LCI) Workshop: Sensing, Reconstruction, and Analysis | Half day, afternoon | Workshop |
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DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision | Session 3A | 12:00–1:00 p.m. EDT |
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Self-Supervised Real-to-Sim Scene Generation | Session 12B | 12:00–1:00 p.m. EDT |
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Video Matting via Consistency-Regularized Graph Neural Networks | Session 4A | 3:00–4:00 p.m. EDT |
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Deep Permutation Equivariant Structure from Motion | Session 5A | 4:00–5:00 p.m. EDT |
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Self-Supervised Object Detection via Generative Image Synthesis | Session 7B | 4:00–5:00 p.m. EDT |
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Self-Calibrating Neural Radiance Fiel | Session 5A | 4:00–5:00 p.m. EDT |
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Active Learning for Deep Object Detection via Probabilistic Modeling | Session 8B | 5:00–6:00 p.m. EDT |
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Video Autoencoder: Self-Supervised Disentanglement of 3D Structure and Motion | Session 8B | 5:00–6:00 p.m. EDT |
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Physics-Based Human Motion Estimation and Synthesis from Videos | Session 9B | 5:00–6:00 p.m. EDT |
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Learning Indoor Reverse Rendering with 3D Spatially Varying Lighting | Session 10A | 6:00–7:00 p.m. EDT |
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3DStyleNet: Creating 3D Shapes with Geometrics and Texture Style Variations | Session 10A | 6:00–7:00 p.m. EDT |
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GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds | Session 11A | 7:00–8:00 p.m. EDT |
T-AutoML: Automated Machine Learning for Lesion Segmentation Using Transformers in 3D Medical Imaging | Session 3B | 7:00–8:00 p.m. EDT |
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Self-Supervised Real-to-Sim Scene Generation | Session 12A | 8:00– 9:00 p.m. EDT |
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