120 citations · 350 across the 25 of their papers we have counts for
27 papers
Decision Making for Human-in-the-loop Robotic Agents via Uncertainty-Aware Reinforcement Learning
Siddharth Singi, Zhanpeng He, Alvin Pan +5
In a Human-in-the-Loop paradigm, a robotic agent is able to act mostly autonomously in solving a task, but can request help from an external expert when needed. However, knowing wh…
RREx-BoT: Remote Referring Expressions with a Bag of Tricks
Gunnar A. Sigurdsson, Jesse Thomason, Gaurav S. Sukhatme +1
Household robots operate in the same space for years. Such robots incrementally build dynamic maps that can be used for tasks requiring remote object localization. However, benchma…
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation
Vishnu Sashank Dorbala, Gunnar Sigurdsson, Robinson Piramuthu +2
Household environments are visually diverse. Embodied agents performing Vision-and-Language Navigation (VLN) in the wild must be able to handle this diversity, while also following…
Video in 10 Bits: Few-Bit VideoQA for Efficiency and Privacy
Shiyuan Huang, Robinson Piramuthu, Shih-Fu Chang +1
In Video Question Answering (VideoQA), answering general questions about a video requires its visual information. Yet, video often contains redundant information irrelevant to the…
A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search
Brandon Trabucco, Gunnar Sigurdsson, Robinson Piramuthu +2
Physically rearranging objects is an important capability for embodied agents. Visual room rearrangement evaluates an agent's ability to rearrange objects in a room to a desired go…
VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator
Ayush Shrivastava, Karthik Gopalakrishnan, Yang Liu +4
Interactive robots navigating photo-realistic environments need to be trained to effectively leverage and handle the dynamic nature of dialogue in addition to the challenges underl…
Self-Attentive 3D Human Pose and Shape Estimation from Videos
Yun-Chun Chen, Marco Piccirilli, Robinson Piramuthu +1
We consider the task of estimating 3D human pose and shape from videos. While existing frame-based approaches have made significant progress, these methods are independently applie…
Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization
Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung +3
Obtaining object response maps is one important step to achieve weakly-supervised semantic segmentation using image-level labels. However, existing methods rely on the classificati…
Weakly-Supervised Semantic Segmentation via Sub-category Exploration
Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung +3
Existing weakly-supervised semantic segmentation methods using image-level annotations typically rely on initial responses to locate object regions. However, such response maps gen…
Mobile Head Tracking for eCommerce and Beyond
Muratcan Cicek, Jinrong Xie, Qiaosong Wang +1
Shopping is difficult for people with motor impairments. This includes online shopping. Proprietary software can emulate mouse and keyboard via head tracking. However, such a solut…
Understanding Image Quality and Trust in Peer-to-Peer Marketplaces
Xiao Ma, Lina Mezghani, Kimberly Wilber +4
As any savvy online shopper knows, second-hand peer-to-peer marketplaces are filled with images of mixed quality. How does image quality impact marketplace outcomes, and can qualit…
Brand > Logo: Visual Analysis of Fashion Brands
M. Hadi Kiapour, Robinson Piramuthu
While lots of people may think branding begins and ends with a logo, fashion brands communicate their uniqueness through a wide range of visual cues such as color, patterns and sha…
Give me a hint! Navigating Image Databases using Human-in-the-loop Feedback
Bryan A. Plummer, M. Hadi Kiapour, Shuai Zheng +1
In this paper, we introduce an attribute-based interactive image search which can leverage human-in-the-loop feedback to iteratively refine image search results. We study active im…
Adversarial Learning for Fine-grained Image Search
Kevin Lin, Fan Yang, Qiaosong Wang +1
Fine-grained image search is still a challenging problem due to the difficulty in capturing subtle differences regardless of pose variations of objects from fine-grained categories…
ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations
Shuai Zheng, Fan Yang, M. Hadi Kiapour +1
Understanding clothes from a single image has strong commercial and cultural impacts on modern societies. However, this task remains a challenging computer vision problem due to wi…
Conditional Image-Text Embedding Networks
Bryan A. Plummer, Paige Kordas, M. Hadi Kiapour +3
This paper presents an approach for grounding phrases in images which jointly learns multiple text-conditioned embeddings in a single end-to-end model. In order to differentiate te…
Towards the Success Rate of One: Real-time Unconstrained Salient Object Detection
Mahyar Najibi, Fan Yang, Qiaosong Wang +1
In this work, we propose an efficient and effective approach for unconstrained salient object detection in images using deep convolutional neural networks. Instead of generating th…
Visual Search at eBay
Fan Yang, Ajinkya Kale, Yury Bubnov +4
In this paper, we propose a novel end-to-end approach for scalable visual search infrastructure. We discuss the challenges we faced for a massive volatile inventory like at eBay an…
ConceptLearner: Discovering Visual Concepts from Weakly Labeled Image Collections
Bolei Zhou, Vignesh Jagadeesh, Robinson Piramuthu
Discovering visual knowledge from weakly labeled data is crucial to scale up computer vision recognition system, since it is expensive to obtain fully labeled data for a large numb…
Efficient Media Retrieval from Non-Cooperative Queries
Kevin Shih, Wei Di, Vignesh Jagadeesh +1
Text is ubiquitous in the artificial world and easily attainable when it comes to book title and author names. Using the images from the book cover set from the Stanford Mobile Vis…
Im2Fit: Fast 3D Model Fitting and Anthropometrics using Single Consumer Depth Camera and Synthetic Data
Qiaosong Wang, Vignesh Jagadeesh, Bryan Ressler +1
Recent advances in consumer depth sensors have created many opportunities for human body measurement and modeling. Estimation of 3D body shape is particularly useful for fashion e-…
Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and Pose-dependent Priors
Kota Hara, Vignesh Jagadeesh, Robinson Piramuthu
In this work, we propose and address a new computer vision task, which we call fashion item detection, where the aim is to detect various fashion items a person in the image is wea…
HD-CNN: Hierarchical Deep Convolutional Neural Network for Large Scale Visual Recognition
Zhicheng Yan, Hao Zhang, Robinson Piramuthu +4
In image classification, visual separability between different object categories is highly uneven, and some categories are more difficult to distinguish than others. Such difficult…
When relevance is not Enough: Promoting Visual Attractiveness for Fashion E-commerce
Wei Di, Anurag Bhardwaj, Vignesh Jagadeesh +2
Fashion, and especially apparel, is the fastest-growing category in online shopping. As consumers requires sensory experience especially for apparel goods for which their appearanc…