no code implementations • 25 Mar 2022 • Wenbin He, William Surmeier, Arvind Kumar Shekar, Liang Gou, Liu Ren
In this work, we propose a self-supervised pixel representation learning method for semantic segmentation by using visual concepts (i. e., groups of pixels with semantic meanings, such as parts, objects, and scenes) extracted from images.
1 code implementation • CVPR 2022 • Yuyan Li, Yuliang Guo, Zhixin Yan, Xinyu Huang, Ye Duan, Liu Ren
In this paper, we propose a 360 monocular depth estimation pipeline, OmniFusion, to tackle the spherical distortion issue.
Ranked #6 on
Depth Estimation
on Stanford2D3D Panoramic
no code implementations • 18 Feb 2022 • Huan Song, Zeng Dai, Panpan Xu, Liu Ren
GraphQ provides a visual query interface with a query editor and a multi-scale visualization of the results, as well as a user feedback mechanism for refining the results with additional constraints.
no code implementations • 2 Feb 2022 • Yuyan Li, Zhixin Yan, Ye Duan, Liu Ren
In this paper, we propose a novel, model-agnostic, two-stage pipeline for omnidirectional monocular depth estimation.
Ranked #13 on
Depth Estimation
on Stanford2D3D Panoramic
no code implementations • 3 Jan 2022 • Arvind Kumar Shekar, Laureen Lake, Liang Gou, Liu Ren
It is on this space we estimate the novelty of the test samples.
no code implementations • 19 May 2021 • Sascha Hornauer, Ke Li, Stella X. Yu, Shabnam Ghaffarzadegan, Liu Ren
Recent progress in network-based audio event classification has shown the benefit of pre-training models on visual data such as ImageNet.
no code implementations • 1 Jan 2021 • Nanxiang Li, Shabnam Ghaffarzadegan, Liu Ren
We show both theoretically and experimentally, the VAE ensemble objective encourages the linear transformations connecting the VAEs to be trivial transformations, aligning the latent representations of different models to be "alike".
no code implementations • 27 Sep 2020 • Liang Gou, Lincan Zou, Nanxiang Li, Michael Hofmann, Arvind Kumar Shekar, Axel Wendt, Liu Ren
In this work, we propose a visual analytics system, VATLD, equipped with a disentangled representation learning and semantic adversarial learning, to assess, understand, and improve the accuracy and robustness of traffic light detectors in autonomous driving applications.
1 code implementation • 12 Jul 2020 • Bilal Alsallakh, Zhixin Yan, Shabnam Ghaffarzadegan, Zeng Dai, Liu Ren
We propose a measure to compute class similarity in large-scale classification based on prediction scores.
1 code implementation • 3 Jan 2020 • Shen Yan, Huan Song, Nanxiang Li, Lincan Zou, Liu Ren
Unsupervised domain adaptation studies the problem of utilizing a relevant source domain with abundant labels to build predictive modeling for an unannotated target domain.
Ranked #32 on
Domain Generalization
on PACS
no code implementations • ICLR 2020 • Nanxiang Li, Shabnam Ghaffarzadegan, Liu Ren
Recent advancements in unsupervised disentangled representation learning focus on extending the variational autoencoder (VAE) with an augmented objective function to balance the trade-off between disentanglement and reconstruction.
1 code implementation • 23 Nov 2019 • Kaiqiang Song, Bingqing Wang, Zhe Feng, Liu Ren, Fei Liu
In this paper, we present a neural summarization model that, by learning from single human abstracts, can produce a broad spectrum of summaries ranging from purely extractive to highly generative ones.
Ranked #11 on
Text Summarization
on GigaWord
2 code implementations • 23 Jul 2019 • Yao Ming, Panpan Xu, Huamin Qu, Liu Ren
The prediction is obtained by comparing the inputs to a few prototypes, which are exemplar cases in the problem domain.
no code implementations • 10 May 2019 • Takanori Fujiwara, Jia-Kai Chou, Shilpika, Panpan Xu, Liu Ren, Kwan-Liu Ma
We enhance an existing incremental PCA method in several ways to ensure its usability for visualizing streaming multidimensional data.
no code implementations • 17 Oct 2017 • Bilal Alsallakh, Amin Jourabloo, Mao Ye, Xiaoming Liu, Liu Ren
We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data.
no code implementations • ICCV 2017 • Amin Jourabloo, Mao Ye, Xiaoming Liu, Liu Ren
Face alignment has witnessed substantial progress in the last decade.
Ranked #11 on
Facial Landmark Detection
on 300W