53 citations · 72 across the 12 of their papers we have counts for
12 papers
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…
DISCO: Adversarial Defense with Local Implicit Functions
Chih-Hui Ho, Nuno Vasconcelos
The problem of adversarial defenses for image classification, where the goal is to robustify a classifier against adversarial examples, is considered. Inspired by the hypothesis th…
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…
Spatio-Temporal Modeling for Flash Memory Channels Using Conditional Generative Nets
Simeng Zheng, Chih-Hui Ho, Wenyu Peng +1
We propose a data-driven approach to modeling the spatio-temporal characteristics of NAND flash memory read voltages using conditional generative networks. The learned model recons…
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…
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…
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…
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…
A New Technique of Camera Calibration: A Geometric Approach Based on Principal Lines
Jen-Hui Chuang, Chih-Hui Ho, Ardian Umam +4
Camera calibration is a crucial prerequisite in many applications of computer vision. In this paper, a new, geometry-based camera calibration technique is proposed, which resolves…