22 citations · 46 across the 6 of their papers we have counts for
6 papers
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-…
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…
Enhancing Visual Fashion Recommendations with Users in the Loop
Anurag Bhardwaj, Vignesh Jagadeesh, Wei Di +2
We describe a completely automated large scale visual recommendation system for fashion. Existing approaches have primarily relied on purely computational models to solving this pr…
Geometric VLAD for Large Scale Image Search
Zixuan Wang, Wei Di, Anurag Bhardwaj +2
We present a novel compact image descriptor for large scale image search. Our proposed descriptor - Geometric VLAD (gVLAD) is an extension of VLAD (Vector of Locally Aggregated Des…