Ronghang Hu | DeepAI

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∙ 01/02/2023

ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Driven by improved architectures and better representation learning fram...

0 Sanghyun Woo, et al. ∙

∙ 12/01/2022

Scaling Language-Image Pre-training via Masking

We present Fast Language-Image Pre-training (FLIP), a simple and more ef...

0 Yanghao Li, et al. ∙

∙ 10/13/2022

Exploring Long-Sequence Masked Autoencoders

Masked Autoencoding (MAE) has emerged as an effective approach for pre-t...

7 Ronghang Hu, et al. ∙

∙ 12/08/2021

FLAVA: A Foundational Language And Vision Alignment Model

State-of-the-art vision and vision-and-language models rely on large-sca...

2 Amanpreet Singh, et al. ∙

∙ 02/22/2021

Transformer is All You Need: Multimodal Multitask Learning with a Unified Transformer

We propose UniT, a Unified Transformer model to simultaneously learn the...

44 Ronghang Hu, et al. ∙

∙ 12/17/2020

Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image

We present Worldsheet, a method for novel view synthesis using just a si...

0 Ronghang Hu, et al. ∙

∙ 03/24/2020

TextCaps: a Dataset for Image Captioning with Reading Comprehension

Image descriptions can help visually impaired people to quickly understa...

0 Oleksii Sidorov, et al. ∙

∙ 11/14/2019

Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA

Many visual scenes contain text that carries crucial information, and it...

22 Ronghang Hu, et al. ∙

∙ 06/02/2019

Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation

Vision-and-Language Navigation (VLN) requires grounding instructions, su...

0 Ronghang Hu, et al. ∙

∙ 05/10/2019

Language-Conditioned Graph Networks for Relational Reasoning

Solving grounded language tasks often requires reasoning about relations...

6 Ronghang Hu, et al. ∙

∙ 07/25/2018

Grounding Visual Explanations

Existing visual explanation generating agents learn to fluently justify ...

0 Lisa Anne Hendricks, et al. ∙

∙ 07/23/2018

Explainable Neural Computation via Stack Neural Module Networks

In complex inferential tasks like question answering, machine learning m...

0 Ronghang Hu, et al. ∙

∙ 06/26/2018

Generating Counterfactual Explanations with Natural Language

Natural language explanations of deep neural network decisions provide a...

1 Lisa Anne Hendricks, et al. ∙

∙ 06/07/2018

Speaker-Follower Models for Vision-and-Language Navigation

Navigation guided by natural language instructions presents a challengin...

0 Daniel Fried, et al. ∙

∙ 11/28/2017

Learning to Segment Every Thing

Existing methods for object instance segmentation require all training i...

0 Ronghang Hu, et al. ∙

∙ 11/17/2017

Grounding Visual Explanations (Extended Abstract)

Existing models which generate textual explanations enforce task relevan...

0 Lisa Anne Hendricks, et al. ∙

∙ 11/30/2016

Modeling Relationships in Referential Expressions with Compositional Modular Networks

People often refer to entities in an image in terms of their relationshi...

0 Ronghang Hu, et al. ∙

∙ 08/30/2016

Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions

Image segmentation from referring expressions is a joint vision and lang...

0 Ronghang Hu, et al. ∙

∙ 03/20/2016

Segmentation from Natural Language Expressions

In this paper we approach the novel problem of segmenting an image based...

0 Ronghang Hu, et al. ∙

∙ 11/13/2015

Natural Language Object Retrieval

In this paper, we address the task of natural language object retrieval,...

0 Ronghang Hu, et al. ∙

∙ 11/12/2015

Grounding of Textual Phrases in Images by Reconstruction

Grounding (i.e. localizing) arbitrary, free-form textual phrases in visu...

0 Anna Rohrbach, et al. ∙

∙ 10/10/2015

Spatial Semantic Regularisation for Large Scale Object Detection

Large scale object detection with thousands of classes introduces the pr...

0 Damian Mrowca, et al. ∙

∙ 07/18/2014

LSDA: Large Scale Detection Through Adaptation

A major challenge in scaling object detection is the difficulty of obtai...

0 Judy Hoffman, et al. ∙

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