CS348n Class Schedule, Spring 2021'22
The videos of the lectures will be posted on Canvas.
Monday

Wednesday

January 3

January 5

Introduction. Traditional 3D modeling pipelines. Computer vision as inverse graphics. Neural 3D representations and neural rendering. Democratization of 3D content creation. Synthetic 3D data for ML training pipelines. Lecture Slides: Intro Reading: SyntheticDataforML 
Classical 3D Geometry Representations. Low level: voxel grids, point clouds, triangular and quad meshes. High level: parametric and implicit boundary representations. Review of some classical geometric concepts (normals, curvature). Lecture Slides: ClassicalGeometry Reading: Old survey, normal estimation 
January 10

January 12

Neural Architectures for Regular Data. Brief review of deep nets and convolutional architectures for images. Sparse convolutions. Transformers. Voxelbased 3D methods for shapes and hierarchical variants. Lecture Slides: NNs,_Voxels Reading: 3DR2N2, 3DVoxTrans, 3DSemSeg, OctGenNet, VoxNet2 
Irregular Geometries: Point Clouds. PointNet and PointNet++. KPConv and other related methods. Sampling issues. Applications to object detection, classification, and segmentation. Lecture Slides: PointClouds Reading: PointNet, PointNet++, DGCNN, VoteNet, FlowNet3D 
January 17


Martin Luther King, Jr., Day (holiday, no classes). 
Introduction to Generative Models (VAEs, deepSDF). Autoencoders and autodecoders. Variational autoencoders. Deep signed distance functions. Lecture Slides: VAE_deepSDF Reading: VarEncoders1, VarEncoders2, VQVAE, DeepMetafunctionals, IMNet, DeepSDF Staff Student Presentation Sample: Slides, Homework 1 out. 
January 24

January 26

Parametric Models. Generative Adversarial Networks (GANs) for 3D. Disentanglement. AtlasNet. InfoGAN, 3DGAN, StyleGAN. Lecture Slides: Param_GANs Reading: GAN1, GAN2, AtlasNet, InfoGAN, WassersteinGAN, StyleGAN1 Student Presentation: Slides1, Slides2, PC Implicit Autoencoder, StructuredImplicits, LocalImplicits 
3D Shape Public Data Sets. Flow and AutoRegressive Models. ShapeNet, PartNet, ... PointFlow, PolyGen. Lecture Slides: DataSets_PolyGen_PointFlow Reading: ShapeNet, PartNet, ABC, PolyGen, PointFlow, CaSPR, MeshODE Student Presentation: ParSeNetSlides, StyleGAN2Slides, StyleGAN3Slides, ParSeNet, StyleGAN2, StyleGAN3 Homework 1 due. Homework 2 out. 
January 31

February 2

Hierarchical Generation of Structure and Geometry. GRASS, StructureNet, ComplementMe. Lecture Slides: Stuct Reading: GRASS, StructureNet, StrucEdit, StructSynth, Abstractions Student Presentation: scene_completion_slides, gradientfields_slides, 
Vector Graphics, Deep Architectures for Meshes. Vector graphics generation, convolutions on meshes. BReps. Lecture Slides: Vector Reading: Im2Vec, MeshCNN, BRepNet, Sketch2CAD Student Presentation: 
February 7

February 9

Pose Equivariance and Invariance in 3D Data. Vector neurons, TFN networks. Lecture Slides: EquivInv Reading: Vector Neurons, TFNs Student Presentation: 
Conditional Generation: 3D Shape Completion. Lecture Slides: CondGen Reading: struct_complete, complement_me, dual_space Student Presentation: SurfaceCNNSlides, MultiViewSlides, ConDorSlides ConDor, SurfaceCNNs, EquivariantMultiView Homework 2 due. Homework 3 out. 
February 14

February 16

Conditional Generation: From Image to Shape. Lecture Slides: Img2Shp Reading: deepmetafunctionals, deeppointset, NOCS, Pix2Surf, DISN, PiFu, no3Dsup, unseenclasses Student Presentation: 
Learning Discrete and Continuous Shape Edits/Deformations. Shaping Latent Spaces. Latent shape differences. Neural shape deformations/edits. Lecture Slides: Deform Reading: MeshODE, ShapeFlow, DeformSyncNet, StructEdit, NeuralCages, DeepMetaHandles, DefAwareRetrieval Student Presentation: PlatonicGAN, D2IMNet, CoReNet Project proposals due. 
February 21

February 23

Presidents' Day (holiday, no classes).

Neural Functions: 3D from 2D Supervision. Neural rendering. Neural radiance fields (NeRFs). Lecture Slides: NeRFs Reading: DiffVolRend, GeomApp, NeRF, NeurText, NeurVol, StableView, StereoMag Student Presentation: 3D Deformation Network, CADDeform, LOGAN Homework 3 due. 
February 28

March 2

Neural Fields and Surfaces. NeRF variations and extensions. Lecture Slides: NeRVar Reading: Nerfies, HyperNerF, NeuS, VolSDF, ObjectNeRF Student Presentation: 
Scene Generation and Object Placement. GRAINS, MetaSim, MetaSim2. Lecture Slides: Scenes Reading: GRAINS, MetaSim, MetaSim2 Student Presentation: 
March 7

March 9

Object/Scene Generation and Language. ShapeGlot, PartGlot. Lecture Slides: Language Reading: ShapeGlot, PartGlot, VLGrammar Student Presentation: BlockGAN, RELATE, PlanIt, DeepGenSynth 
Student Project Presentations. Lecture Slides: Reading: Project due. 