Schedule Broad Area Reading List
Jan 12 Course Intro + intro to 3D representations
Jan 19 1.Representations of 3D data in Modern ML PointNet and PointNet++ Slides (Dylan Turpin)
Local Deep Implicit Functions for 3D Shape Slides (Jun Gao)
Optional: Points2Surf, NOCS, DeepSDF
Jan 26 2.Learning: 3D Shape Modelling PointConv
Dynamic Graph CNN for Learning on Point Clouds Presentation (Mustafa Haiderbhai) Slides
KPConv Presentation (Bin Yang) Slides
DeepSDF Presentation (Tianchang Shen) Slides
Optional: PCT: Point Cloud Transformer, Learning Deformable Tetrahedral Meshes for 3D Reconstruction, PIE-NET
Feb 2 3.Computational Efficiency in Processing of 3D Data + Scene Understanding Guest speaker: Dr. Chris Choy (Nvidia) presenting MinowskiNets
Virtual Multi-view Fusion for 3D Semantic Segmentation Presentation (Xiang Cao) Slides
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans Presentation (Haoping Xu) Slides
Optional: Unsupervised part representation by Flow Capsules, OccuSeg, SparseConvNet
Feb 9 4.Generative Modelling in 3D Learning Generative Models of 3D Structures Presentation (Tao Wu) Slides
PolyGen Presentation (Alexander Tessier) Slides
Learning Gradient Fields for Shape Generation Presentation (Andrej Janda)
ShapeAssembly Presentation (Zhoujie Zhao) Slides
AtlasNet Presentation (Varun Pandya) Slides
Optional: StructureNet
Feb 16 5.Differentiable Rendering Differentiable Rendering: A Survey Presentation (Ze Yang) Slides
Differentiable Monte Carlo Ray Tracing through Edge Sampling Presentation (Jingkang Wang)
Multiview Neural Surface Reconstruction with Implicit Lighting and Material Presentation (Wenzhi Guo) Slides
Differentiable Volumetric Rendering Presentation (Sara Sabour) Slides
Optional: Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning, Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer
Feb 23 6.Neural Rendering NeRF Neural Volume Rendering: NeRF And Beyond
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections Presentation (Gary Leung) Slides
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations Presentation (Shayan Shekarforoush) Slides
Neural Reflectance Fields for Appearance Acquisition Presentation (Zian Wang) Slides
Optional: NeRF Explosion 2020
Mar 2 7.NeRF Applications NSVF: Neural Sparse Voxel Fields Presentation (Tianxing Li) Slides
NeRFies: Deformable Neural Radiance Fields Presentation (Yun-Chun Chen) Slides
iNeRF: Inverting Neural Radiance Fields for Pose Estimation Presentation (Bin Shi) Slides
Optional: NASA: Neural Articulated Shape Approximation, GRF: Learning a General Radiance Field for 3D Scene Representation and Rendering
Mar 9 8.Equivariance and Invariance Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Gauge Equivariant Mesh CNNs Presentation (Otman Benchekroun) Slides
On Learning Sets of Symmetric Elements Presentation (Dmitrii Shubin) Slides
CNNs on Surfaces using Rotation-Equivariant Features Presentation (Shichen Lu) Slides
Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic Flows
Mar 16 9.Unsupervised 3D learning Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild Presentation (Brendan Kolisnik) Slides
Canonical Capsules: Unsupervised Capsules in Canonical Pose Presentation (Ioannis Xarchakos Slides
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
Learning Delaunay Surface Elements for Mesh Reconstruction Presentation (Brendan Duke) Slides
Optional: KeypointNet: Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning, Unsupervised Geometry-Aware Representation Learning for 3D Human Pose Estimation, Unsupervised part representation by Flow Capsules, Weakly-Supervised 3D Human Pose Learning via Multi-View Images in the Wild
Mar 23 10.Geometric Deep Learning Beyond Computer Vision Guest speaker: Prof. Jonathan Kelly presenting Self-Supervised Deep Pose Corrections for Robust Visual Odometry
Isometric Transformation Invariant and Equivariant Graph Convolutional Networks Presentation (Sejin Kim) Slides
Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation Presentation (William Ngo) Slides
Optional: 6-DOF GraspNet: Variational Grasp Generation for Object Manipulation, DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion, Dense Object Nets, KeyPoint Affordances for Category-Level Robotic Manipulation
Mar 30 11.3D vision in Robotics Fast end-to-end learning on protein surfaces Presentation (Youheng Ge) Slides
Relational inductive biases, deep learning, and graph networks Presentation (Seung Wook Kim) Slides
LanczosNet: Multi-Scale Deep Graph Convolutional Networks Presentation (Juan Carrillo) Slides
SIREN: Implicit Neural Representations with Periodic Activation Functions Presentation (Zikun Chen) Slides
Optional: RigNet: Neural Rigging for Articulated Characters, 3DGV Seminar: Michael Bronstein -- Geometric Deep Learning
Apr 6 Project Presentations.
Apr 10 Take Home midterm.
Apr 12 Project Presentation Buffer.