CS331B: Representation Learning in Computer Vision

Autumn Quarter 2016, Stanford University

Project Presentation Information

Date: Monday, December 12, 2016

Time: 3:30 - 6:30 PM

Location: Hewlett 200

List of Projects

Geometric Concept Acquisition by Deep Reinforcement Learning
Alex Kuefler

Representation Learning for Modeling and Control of Flexible Manipulators
Joey Greer

Deep Learning on Point Sets for 3D Classification and Segmentation
Charles Ruizhongtai Qi

Feedback based Neural Networks
Te-Lin Wu and William Shen

Learning Deep Representations for Human Activity in Video
Shikhar Shrestha

Hidden Cues: Deep Learning for Alzheimer's Disease Classification
Tanya Glozman and Orly Liba

Object Detection without Forgetting
Vishakh Hegde and Manik Dhar

Adding Perceptual Losses of Objects to Fast Style Transfer Networks
Jee Ian Tam

Multi-view Indoor Scene Layout Estimation
Yuanfang Wang

Fast Bilateral Solver for Semantic Video Segmentation
Max Wang and Shannon Kao

Image Denoising with Deep Convolutional Generative Adversarial Networks and Symmetric Connections
Aojia Zhao

Improving Image Classification by Understanding Semantic Hierarchies with Gated CNNs
Lisa Wang and Ajay Sohmshetty

Visualizing and Understanding Stochastic Depth Networks
Russel Kaplan, Raphael Palefsky-Smith, and Liu Jiang

Bottleneck Conditional Density Estimators
Rui Shu