150 citations · 326 across the 15 of their papers we have counts for
8 papers · 1 filter
ArK: Augmented Reality with Knowledge Interactive Emergent Ability
Qiuyuan Huang, Jae Sung Park, Abhinav Gupta +8
Despite the growing adoption of mixed reality and interactive AI agents, it remains challenging for these systems to generate high quality 2D/3D scenes in unseen environments. The…
Training Vision-Language Transformers from Captions
Liangke Gui, Yingshan Chang, Qiuyuan Huang +4
Vision-Language Transformers can be learned without low-level human labels (e.g. class labels, bounding boxes, etc). Existing work, whether explicitly utilizing bounding boxes or p…
Object-driven Text-to-Image Synthesis via Adversarial Training
Wenbo Li, Pengchuan Zhang, Lei Zhang +4
In this paper, we propose Object-driven Attentive Generative Adversarial Newtorks (Obj-GANs) that allow object-centered text-to-image synthesis for complex scenes. Following the tw…
Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation
Xin Wang, Qiuyuan Huang, Asli Celikyilmaz +5
Vision-language navigation (VLN) is the task of navigating an embodied agent to carry out natural language instructions inside real 3D environments. In this paper, we study how to…
Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation
Qiuyuan Huang, Zhe Gan, Asli Celikyilmaz +3
We propose a hierarchically structured reinforcement learning approach to address the challenges of planning for generating coherent multi-sentence stories for the visual storytell…
Generating Diverse and Accurate Visual Captions by Comparative Adversarial Learning
Dianqi Li, Qiuyuan Huang, Xiaodong He +2
We study how to generate captions that are not only accurate in describing an image but also discriminative across different images. The problem is both fundamental and interesting…
Structured Memory based Deep Model to Detect as well as Characterize Novel Inputs
Pratik Prabhanjan Brahma, Qiuyuan Huang, Dapeng Wu
While deep learning has pushed the boundaries in various machine learning tasks, the current models are still far away from replicating many functions that a normal human brain can…
Tensor Product Generation Networks for Deep NLP Modeling
Qiuyuan Huang, Paul Smolensky, Xiaodong He +2
We present a new approach to the design of deep networks for natural language processing (NLP), based on the general technique of Tensor Product Representations (TPRs) for encoding…