activity
20192022
most citedSolving Long-tailed Recognition with Deep Realistic Taxonomic Classifier

4 citations · 5 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

YORO -- Lightweight End to End Visual Grounding

Chih-Hui Ho, Srikar Appalaraju, Bhavan Jasani +2

We present YORO - a multi-modal transformer encoder-only architecture for the Visual Grounding (VG) task. This task involves localizing, in an image, an object referred via natural…

cs.CV2021

OOWL500: Overcoming Dataset Collection Bias in the Wild

Brandon Leung, Chih-Hui Ho, Amir Persekian +5

The hypothesis that image datasets gathered online "in the wild" can produce biased object recognizers, e.g. preferring professional photography or certain viewing angles, is studi…

cs.CV2021

Black-Box Test-Time Shape REFINEment for Single View 3D Reconstruction

Brandon Leung, Chih-Hui Ho, Nuno Vasconcelos

Much recent progress has been made in reconstructing the 3D shape of an object from an image of it, i.e. single view 3D reconstruction. However, it has been suggested that current…

cs.CV2020

Contrastive Learning with Adversarial Examples

Chih-Hui Ho, Nuno Vasconcelos

Contrastive learning (CL) is a popular technique for self-supervised learning (SSL) of visual representations. It uses pairs of augmentations of unlabeled training examples to defi…

cs.CV20204 cited

Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier

Tz-Ying Wu, Pedro Morgado, Pei Wang +2

Long-tail recognition tackles the natural non-uniformly distributed data in real-world scenarios. While modern classifiers perform well on populated classes, its performance degrad…

cs.CV2020

Exploit Clues from Views: Self-Supervised and Regularized Learning for Multiview Object Recognition

Chih-Hui Ho, Bo Liu, Tz-Ying Wu +1

Multiview recognition has been well studied in the literature and achieves decent performance in object recognition and retrieval task. However, most previous works rely on supervi…