activity
20172022
most citedMen Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints

124 citations · 221 across the 11 of their papers we have counts for

collaborators

17 papers

cs.CV20201 cited

Chair Segments: A Compact Benchmark for the Study of Object Segmentation

Leticia Pinto-Alva, Ian K. Torres, Rosangel Garcia +2

Over the years, datasets and benchmarks have had an outsized influence on the design of novel algorithms. In this paper, we introduce ChairSegments, a novel and compact semi-synthe…

cs.CV202021 cited

General Multi-label Image Classification with Transformers

Jack Lanchantin, Tianlu Wang, Vicente Ordonez +1

Multi-label image classification is the task of predicting a set of labels corresponding to objects, attributes or other entities present in an image. In this work we propose the C…

cs.CV2020

Visual News: Benchmark and Challenges in News Image Captioning

Fuxiao Liu, Yinghan Wang, Tianlu Wang +1

We propose Visual News Captioner, an entity-aware model for the task of news image captioning. We also introduce Visual News, a large-scale benchmark consisting of more than one mi…

cs.CL20207 cited

Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation

Tianlu Wang, Xi Victoria Lin, Nazneen Fatema Rajani +3

Word embeddings derived from human-generated corpora inherit strong gender bias which can be further amplified by downstream models. Some commonly adopted debiasing approaches, inc…

cs.LG2020

Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning

Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi +1

In this paper we revisit the idea of pseudo-labeling in the context of semi-supervised learning where a learning algorithm has access to a small set of labeled samples and a large…

cs.CV201913 cited

Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries

Fuwen Tan, Paola Cascante-Bonilla, Xiaoxiao Guo +3

This paper explores the task of interactive image retrieval using natural language queries, where a user progressively provides input queries to refine a set of retrieval results.…