Search Results for author: Zilong Zheng

Found 17 papers, 6 papers with code

SHARP: Search-Based Adversarial Attack for Structured Prediction

no code implementations Findings (NAACL) 2022 Liwen Zhang, Zixia Jia, Wenjuan Han, Zilong Zheng, Kewei Tu

Adversarial attack of structured prediction models faces various challenges such as the difficulty of perturbing discrete words, the sentence quality issue, and the sensitivity of outputs to small perturbations.

Adversarial Attack Dependency Parsing +2

Energy-Based Generative Cooperative Saliency Prediction

1 code implementation25 Jun 2021 Jing Zhang, Jianwen Xie, Zilong Zheng, Nick Barnes

In this paper, to model the uncertainty of visual saliency, we study the saliency prediction problem from the perspective of generative models by learning a conditional probability distribution over the saliency map given an input image, and treating the saliency prediction as a sampling process from the learned distribution.

Saliency Prediction

Patchwise Generative ConvNet: Training Energy-Based Models From a Single Natural Image for Internal Learning

no code implementations CVPR 2021 Zilong Zheng, Jianwen Xie, Ping Li

Exploiting internal statistics of a single natural image has long been recognized as a significant research paradigm where the goal is to learn the distribution of patches within the image without relying on external training data.

Image Generation Super-Resolution

Learning Triadic Belief Dynamics in Nonverbal Communication from Videos

1 code implementation CVPR 2021 Lifeng Fan, Shuwen Qiu, Zilong Zheng, Tao Gao, Song-Chun Zhu, Yixin Zhu

By aggregating different beliefs and true world states, our model essentially forms "five minds" during the interactions between two agents.

Scene Understanding

Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation

no code implementations7 Mar 2021 Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu

This paper studies the unsupervised cross-domain translation problem by proposing a generative framework, in which the probability distribution of each domain is represented by a generative cooperative network that consists of an energy-based model and a latent variable model.

Translation Unsupervised Image-To-Image Translation

Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler

no code implementations29 Dec 2020 Jianwen Xie, Zilong Zheng, Ping Li

In this paper, we propose to learn a variational auto-encoder (VAE) to initialize the finite-step MCMC, such as Langevin dynamics that is derived from the energy function, for efficient amortized sampling of the EBM.

Joint Inference of States, Robot Knowledge, and Human (False-)Beliefs

no code implementations25 Apr 2020 Tao Yuan, Hangxin Liu, Lifeng Fan, Zilong Zheng, Tao Gao, Yixin Zhu, Song-Chun Zhu

Aiming to understand how human (false-)belief--a core socio-cognitive ability--would affect human interactions with robots, this paper proposes to adopt a graphical model to unify the representation of object states, robot knowledge, and human (false-)beliefs.

Object Tracking

Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification

1 code implementation CVPR 2021 Jianwen Xie, Yifei Xu, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu

We propose a generative model of unordered point sets, such as point clouds, in the form of an energy-based model, where the energy function is parameterized by an input-permutation-invariant bottom-up neural network.

General Classification Point Cloud Classification +2

Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning

no code implementations7 Feb 2019 Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu

This paper studies the problem of learning the conditional distribution of a high-dimensional output given an input, where the output and input may belong to two different domains, e. g., the output is a photo image and the input is a sketch image.

Image-to-Image Translation

Learning Dynamic Generator Model by Alternating Back-Propagation Through Time

no code implementations27 Dec 2018 Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu

The non-linear transformation of this transition model can be parametrized by a feedforward neural network.

Learning Descriptor Networks for 3D Shape Synthesis and Analysis

1 code implementation CVPR 2018 Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu

This paper proposes a 3D shape descriptor network, which is a deep convolutional energy-based model, for modeling volumetric shape patterns.

3D Object Super-Resolution

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