4 citations · 5 across the 5 of their papers we have counts for
10 papers · 1 filter
Long-Tailed Anomaly Detection with Learnable Class Names
Chih-Hui Ho, Kuan-Chuan Peng, Nuno Vasconcelos
Anomaly detection (AD) aims to identify defective images and localize their defects (if any). Ideally, AD models should be able to detect defects over many image classes; without r…
ProTeCt: Prompt Tuning for Taxonomic Open Set Classification
Tz-Ying Wu, Chih-Hui Ho, Nuno Vasconcelos
Visual-language foundation models, like CLIP, learn generalized representations that enable zero-shot open-set classification. Few-shot adaptation methods, based on prompt tuning,…
Toward Unsupervised Realistic Visual Question Answering
Yuwei Zhang, Chih-Hui Ho, Nuno Vasconcelos
The problem of realistic VQA (RVQA), where a model has to reject unanswerable questions (UQs) and answer answerable ones (AQs), is studied. We first point out 2 drawbacks in curren…
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…
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…
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…