Single-Stage Visual Relationship Learning using Conditional Queries

no code implementations • 9 Jun 2023 • Alakh Desai, Tz-Ying Wu, Subarna Tripathi, Nuno Vasconcelos

Research in scene graph generation (SGG) usually considers two-stage models, that is, detecting a set of entities, followed by combining them and labeling all possible relationships.

Graph Generation Multi-Task Learning +1

ProTeCt: Prompt Tuning for Taxonomic Open Set Classification

1 code implementation • 4 Jun 2023 • Tz-Ying Wu, Chih-Hui Ho, Nuno Vasconcelos

A new Prompt Tuning for Hierarchical Consistency (ProTeCt) technique is then proposed to calibrate classification across label set granularities.

Classification open-set classification

Class-Incremental Learning with Strong Pre-trained Models

1 code implementation • CVPR 2022 • Tz-Ying Wu, Gurumurthy Swaminathan, Zhizhong Li, Avinash Ravichandran, Nuno Vasconcelos, Rahul Bhotika, Stefano Soatto

We hypothesize that a strong base model can provide a good representation for novel classes and incremental learning can be done with small adaptations.

Class Incremental Learning Incremental Learning

Learning of Visual Relations: The Devil is in the Tails

no code implementations • ICCV 2021 • Alakh Desai, Tz-Ying Wu, Subarna Tripathi, Nuno Vasconcelos

Significant effort has been recently devoted to modeling visual relations.

Graph Generation Scene Graph Generation

Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier

1 code implementation • ECCV 2020 • Tz-Ying Wu, Pedro Morgado, Pei Wang, Chih-Hui Ho, Nuno Vasconcelos

Motivated by this, a deep realistic taxonomic classifier (Deep-RTC) is proposed as a new solution to the long-tail problem, combining realism with hierarchical predictions.

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

1 code implementation • CVPR 2020 • Chih-Hui Ho, Bo Liu, Tz-Ying Wu, Nuno Vasconcelos

Multiview recognition has been well studied in the literature and achieves decent performance in object recognition and retrieval task.

Object Object Recognition +2

Explainable Object-induced Action Decision for Autonomous Vehicles

1 code implementation • CVPR 2020 • Yiran Xu, Xiaoyin Yang, Lihang Gong, Hsuan-Chu Lin, Tz-Ying Wu, Yunsheng Li, Nuno Vasconcelos

The new paradigm lies between the end-to-end and pipelined approaches, and is inspired by how humans solve the problem.

Autonomous Driving Object +1

Liquid Pouring Monitoring via Rich Sensory Inputs

no code implementations • ECCV 2018 • Tz-Ying Wu, Juan-Ting Lin, Tsun-Hsuang Wang, Chan-Wei Hu, Juan Carlos Niebles, Min Sun

In the closed-loop system, the ability to monitor the state of the task via rich sensory information is important but often less studied.

Anticipating Daily Intention using On-Wrist Motion Triggered Sensing

1 code implementation • ICCV 2017 • Tz-Ying Wu, Ting-An Chien, Cheng-Sheng Chan, Chan-Wei Hu, Min Sun

The core of the system is a novel Recurrent Neural Network (RNN) and Policy Network (PN), where the RNN encodes visual and motion observation to anticipate intention, and the PN parsimoniously triggers the process of visual observation to reduce computation requirement.