Search Results for author: Raymond A. Yeh

Found 29 papers, 17 papers with code

Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields

no code implementations2 Apr 2024 Joshua Ahn, Haochen Wang, Raymond A. Yeh, Greg Shakhnarovich

Scale-ambiguity in 3D scene dimensions leads to magnitude-ambiguity of volumetric densities in neural radiance fields, i. e., the densities double when scene size is halved, and vice versa.

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs

1 code implementation19 Mar 2024 Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar

On complex downstream tasks with limited data, such as fluid flow simulations and fluid-structure interactions, we found CoDA-NO to outperform existing methods on the few-shot learning task by over $36\%$.

Few-Shot Learning Self-Supervised Learning

AmbiGen: Generating Ambigrams from Pre-trained Diffusion Model

no code implementations5 Dec 2023 Boheng Zhao, Rana Hanocka, Raymond A. Yeh

Ambigrams are calligraphic designs that have different meanings depending on the viewing orientation.

IMMA: Immunizing text-to-image Models against Malicious Adaptation

2 code implementations30 Nov 2023 Amber Yijia Zheng, Raymond A. Yeh

Advancements in text-to-image models and fine-tuning methods have led to the increasing risk of malicious adaptation, i. e., fine-tuning to generate harmful unauthorized content.

Data Poisoning

Truly Scale-Equivariant Deep Nets with Fourier Layers

1 code implementation NeurIPS 2023 Md Ashiqur Rahman, Raymond A. Yeh

In computer vision, models must be able to adapt to changes in image resolution to effectively carry out tasks such as image segmentation; This is known as scale-equivariance.

Image Segmentation Semantic Segmentation

Making Vision Transformers Truly Shift-Equivariant

no code implementations25 May 2023 Renan A. Rojas-Gomez, Teck-Yian Lim, Minh N. Do, Raymond A. Yeh

For computer vision, Vision Transformers (ViTs) have become one of the go-to deep net architectures.

Image Classification Semantic Segmentation

Tree Instance Segmentation With Temporal Contour Graph

no code implementations CVPR 2023 Adnan Firoze, Cameron Wingren, Raymond A. Yeh, Bedrich Benes, Daniel Aliaga

We present a novel approach to perform instance segmentation, and counting, for densely packed self-similar trees using a top-view RGB image sequence.

Benchmarking Instance Segmentation +2

Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation

1 code implementation CVPR 2023 Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, Greg Shakhnarovich

We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through the Jacobian of a differentiable renderer, which we instantiate to be a voxel radiance field.

3D Generation Text to 3D

Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks

1 code implementation14 Oct 2022 Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing, Minh N. Do, Raymond A. Yeh

We propose learnable polyphase sampling (LPS), a pair of learnable down/upsampling layers that enable truly shift-invariant and equivariant convolutional networks.

Image Classification Segmentation +1

TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation

no code implementations11 Oct 2022 William Gao, April Wang, Gal Metzer, Raymond A. Yeh, Rana Hanocka

We present TetGAN, a convolutional neural network designed to generate tetrahedral meshes.

Text-Free Learning of a Natural Language Interface for Pretrained Face Generators

1 code implementation8 Sep 2022 Xiaodan Du, Raymond A. Yeh, Nicholas Kolkin, Eli Shechtman, Greg Shakhnarovich

We propose Fast text2StyleGAN, a natural language interface that adapts pre-trained GANs for text-guided human face synthesis.

Face Generation

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.

Inductive Bias Translation

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.

Benchmarking 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 +1

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 Reinforcement Learning (RL) +2

Inverting Adversarially Robust Networks for Image Synthesis

1 code implementation13 Jun 2021 Renan A. Rojas-Gomez, Raymond A. Yeh, Minh N. Do, Anh Nguyen

Despite unconditional feature inversion being the foundation of many image synthesis applications, training an inverter demands a high computational budget, large decoding capacity and imposing conditions such as autoregressive priors.

Anomaly Detection Deep Feature Inversion +3

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 +2

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 Human Pose Estimation 3D Pose Estimation +3

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

2 code implementations31 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 +1

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.

Optical Flow Estimation Video Prediction

Semantic Image Inpainting with Deep Generative Models

7 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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