Search Results for author: Raymond A. Yeh

Found 18 papers, 10 papers with code

Equivariance Discovery by Learned Parameter-Sharing

1 code implementation7 Apr 2022 Raymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, Alexander G. Schwing

Designing equivariance as an inductive bias into deep-nets has been a prominent approach to build effective models, e. g., a convolutional neural network incorporates translation equivariance.


Total Variation Optimization Layers for Computer Vision

1 code implementation7 Apr 2022 Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren, Alexander G. Schwing

To study question (a), in this work, we propose total variation (TV) minimization as a layer for computer vision.

Edge Detection Image Classification +2

Adapting CLIP For Phrase Localization Without Further Training

1 code implementation7 Apr 2022 Jiahao Li, Greg Shakhnarovich, Raymond A. Yeh

Our method for phrase localization requires no human annotations or additional training.

EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search

1 code implementation24 Nov 2021 Qian Jiang, Xiaofan Zhang, Deming Chen, Minh N. Do, Raymond A. Yeh

In this work, we propose End-to-end Hardware-aware DNAS (EH-DNAS), a seamless integration of end-to-end hardware benchmarking, and fully automated DNAS to deliver hardware-efficient deep neural networks on various platforms, including Edge GPUs, Edge TPUs, Mobile CPUs, and customized accelerators.

Neural Architecture Search

Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning

no code implementations6 Aug 2021 Iou-Jen Liu, Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing

We evaluate `semantic tracklets' on the visual multi-agent particle environment (VMPE) and on the challenging visual multi-agent GFootball environment.

Multi-agent Reinforcement Learning reinforcement-learning

Cooperative Exploration for Multi-Agent Deep Reinforcement Learning

no code implementations23 Jul 2021 Iou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing

To address this shortcoming, in this paper, we propose cooperative multi-agent exploration (CMAE): agents share a common goal while exploring.

reinforcement-learning SMAC +1

Inverting Adversarially Robust Networks for Image Synthesis

no code implementations13 Jun 2021 Renan A. Rojas-Gomez, Raymond A. Yeh, Minh N. Do, Anh Nguyen

To address these limitations, we propose the use of adversarially robust representations as a perceptual primitive for feature inversion.

Anomaly Detection Image Denoising +2

High-Throughput Synchronous Deep RL

1 code implementation NeurIPS 2020 Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing

In contrast, asynchronous methods achieve high throughput but suffer from stability issues and lower sample efficiency due to `stale policies.'

Atari Games reinforcement-learning

Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning

no code implementations NeurIPS 2020 Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing

Existing semi-supervised learning (SSL) algorithms use a single weight to balance the loss of labeled and unlabeled examples, i. e., all unlabeled examples are equally weighted.

Chirality Nets for Human Pose Regression

1 code implementation NeurIPS 2019 Raymond A. Yeh, Yuan-Ting Hu, Alexander G. Schwing

We propose Chirality Nets, a family of deep nets that is equivariant to the "chirality transform," i. e., the transformation to create a chiral pair.

3D Pose Estimation Activity Recognition +1

PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning

1 code implementation31 Oct 2019 Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing

Sample efficiency and scalability to a large number of agents are two important goals for multi-agent reinforcement learning systems.

Multi-agent Reinforcement Learning reinforcement-learning

Diverse Generation for Multi-Agent Sports Games

no code implementations CVPR 2019 Raymond A. Yeh, Alexander G. Schwing, Jonathan Huang, Kevin Murphy

In this paper, we propose a new generative model for multi-agent trajectory data, focusing on the case of multi-player sports games.

Unsupervised Textual Grounding: Linking Words to Image Concepts

no code implementations CVPR 2018 Raymond A. Yeh, Minh N. Do, Alexander G. Schwing

Textual grounding, i. e., linking words to objects in images, is a challenging but important task for robotics and human-computer interaction.

Two-sample testing

Video Frame Synthesis using Deep Voxel Flow

3 code implementations ICCV 2017 Ziwei Liu, Raymond A. Yeh, Xiaoou Tang, Yiming Liu, Aseem Agarwala

We combine the advantages of these two methods by training a deep network that learns to synthesize video frames by flowing pixel values from existing ones, which we call deep voxel flow.

Frame Optical Flow Estimation

Semantic Image Inpainting with Deep Generative Models

6 code implementations CVPR 2017 Raymond A. Yeh, Chen Chen, Teck Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do

In this paper, we propose a novel method for semantic image inpainting, which generates the missing content by conditioning on the available data.

Image Inpainting

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