Search Results for author: Brandon Yang

Found 7 papers, 4 papers with code

Streaming Object Detection for 3-D Point Clouds

no code implementations ECCV 2020 Wei Han, Zhengdong Zhang, Benjamin Caine, Brandon Yang, Christoph Sprunk, Ouais Alsharif, Jiquan Ngiam, Vijay Vasudevan, Jonathon Shlens, Zhifeng Chen

This built-in data capture latency is artificial, and based on treating the point cloud as a camera image in order to leverage camera-inspired architectures.

Action Recognition Autonomous Vehicles +2

StarNet: Targeted Computation for Object Detection in Point Clouds

no code implementations29 Aug 2019 Jiquan Ngiam, Benjamin Caine, Wei Han, Brandon Yang, Yuning Chai, Pei Sun, Yin Zhou, Xi Yi, Ouais Alsharif, Patrick Nguyen, Zhifeng Chen, Jonathon Shlens, Vijay Vasudevan

We show how our redesign---namely using only local information and using sampling instead of learned proposals---leads to a significantly more flexible and adaptable system: we demonstrate how we can vary the computational cost of a single trained StarNet without retraining, and how we can target proposals towards areas of interest with priors and heuristics.

3D Object Detection Pedestrian Detection +1

Using Videos to Evaluate Image Model Robustness

no code implementations22 Apr 2019 Keren Gu, Brandon Yang, Jiquan Ngiam, Quoc Le, Jonathon Shlens

Compared to previous studies on adversarial examples and synthetic distortions, natural robustness captures a more diverse set of common image transformations that occur in the natural environment.

CondConv: Conditionally Parameterized Convolutions for Efficient Inference

8 code implementations NeurIPS 2019 Brandon Yang, Gabriel Bender, Quoc V. Le, Jiquan Ngiam

We demonstrate that scaling networks with CondConv improves the performance and inference cost trade-off of several existing convolutional neural network architectures on both classification and detection tasks.

General Classification Image Classification +1

Surprising Negative Results for Generative Adversarial Tree Search

3 code implementations ICLR 2019 Kamyar Azizzadenesheli, Brandon Yang, Weitang Liu, Zachary C. Lipton, Animashree Anandkumar

We deploy this model and propose generative adversarial tree search (GATS) a deep RL algorithm that learns the environment model and implements Monte Carlo tree search (MCTS) on the learned model for planning.

Atari Games

MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs

11 code implementations11 Dec 2017 Pranav Rajpurkar, Jeremy Irvin, Aarti Bagul, Daisy Ding, Tony Duan, Hershel Mehta, Brandon Yang, Kaylie Zhu, Dillon Laird, Robyn L. Ball, Curtis Langlotz, Katie Shpanskaya, Matthew P. Lungren, Andrew Y. Ng

To evaluate models robustly and to get an estimate of radiologist performance, we collect additional labels from six board-certified Stanford radiologists on the test set, consisting of 207 musculoskeletal studies.

Anomaly Detection

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