Search Results for author: Jialiang Wang

Found 22 papers, 7 papers with code

VEnvision3D: A Synthetic Perception Dataset for 3D Multi-Task Model Research

no code implementations29 Feb 2024 Jiahao Zhou, Chen Long, Yue Xie, Jialiang Wang, Boheng Li, Haiping Wang, Zhe Chen, Zhen Dong

Therefore, such a unique attribute can assist in exploring the potential for the multi-task model and even the foundation model without separate training methods.

3D Reconstruction Attribute +2

Mini-Hes: A Parallelizable Second-order Latent Factor Analysis Model

1 code implementation19 Feb 2024 Jialiang Wang, Weiling Li, Yurong Zhong, Xin Luo

The performance of an LFA model relies heavily on its training process, which is a non-convex optimization.

Recommendation Systems

FaKnow: A Unified Library for Fake News Detection

1 code implementation27 Jan 2024 Yiyuan Zhu, Yongjun Li, Jialiang Wang, Ming Gao, Jiali Wei

Over the past years, a large number of fake news detection algorithms based on deep learning have emerged.

Fake News Detection

Efficient Quantization Strategies for Latent Diffusion Models

no code implementations9 Dec 2023 Yuewei Yang, Xiaoliang Dai, Jialiang Wang, Peizhao Zhang, Hongbo Zhang

By treating the quantization discrepancy as relative noise and identifying sensitive part(s) of a model, we propose an efficient quantization approach encompassing both global and local strategies.

Quantization Text-to-Image Generation

ControlRoom3D: Room Generation using Semantic Proxy Rooms

no code implementations8 Dec 2023 Jonas Schult, Sam Tsai, Lukas Höllein, Bichen Wu, Jialiang Wang, Chih-Yao Ma, Kunpeng Li, Xiaofang Wang, Felix Wimbauer, Zijian He, Peizhao Zhang, Bastian Leibe, Peter Vajda, Ji Hou

Central to our approach is a user-defined 3D semantic proxy room that outlines a rough room layout based on semantic bounding boxes and a textual description of the overall room style.

A Practical Stereo Depth System for Smart Glasses

no code implementations CVPR 2023 Jialiang Wang, Daniel Scharstein, Akash Bapat, Kevin Blackburn-Matzen, Matthew Yu, Jonathan Lehman, Suhib Alsisan, Yanghan Wang, Sam Tsai, Jan-Michael Frahm, Zijian He, Peter Vajda, Michael F. Cohen, Matt Uyttendaele

We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with a fallback to monocular depth estimation when rectification is unreliable.

Monocular Depth Estimation Stereo Depth Estimation

Consistent Direct Time-of-Flight Video Depth Super-Resolution

1 code implementation CVPR 2023 Zhanghao Sun, Wei Ye, Jinhui Xiong, Gyeongmin Choe, Jialiang Wang, Shuochen Su, Rakesh Ranjan

We believe the methods and dataset are beneficial to a broad community as dToF depth sensing is becoming mainstream on mobile devices.

Super-Resolution

A Practical Second-order Latent Factor Model via Distributed Particle Swarm Optimization

no code implementations12 Aug 2022 Jialiang Wang, Yurong Zhong, Weiling Li

Determining these hyperparameters is time-consuming and it largely reduces the practicability of an SLF model.

UMSNet: An Universal Multi-sensor Network for Human Activity Recognition

no code implementations24 May 2022 Jialiang Wang, Haotian Wei, Yi Wang, Shu Yang, Chi Li

Human activity recognition (HAR) based on multimodal sensors has become a rapidly growing branch of biometric recognition and artificial intelligence.

Human Activity Recognition Time Series +2

FBNetV5: Neural Architecture Search for Multiple Tasks in One Run

no code implementations19 Nov 2021 Bichen Wu, Chaojian Li, Hang Zhang, Xiaoliang Dai, Peizhao Zhang, Matthew Yu, Jialiang Wang, Yingyan Lin, Peter Vajda

To tackle these challenges, we propose FBNetV5, a NAS framework that can search for neural architectures for a variety of vision tasks with much reduced computational cost and human effort.

Classification Image Classification +4

Level Set Binocular Stereo with Occlusions

1 code implementation8 Sep 2021 Jialiang Wang, Todd Zickler

Localizing stereo boundaries and predicting nearby disparities are difficult because stereo boundaries induce occluded regions where matching cues are absent.

Occlusion Handling

Interpreting Robust Optimization via Adversarial Influence Functions

no code implementations ICML 2020 Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang

Robust optimization has been widely used in nowadays data science, especially in adversarial training.

Improving Deep Stereo Network Generalization with Geometric Priors

no code implementations25 Aug 2020 Jialiang Wang, Varun Jampani, Deqing Sun, Charles Loop, Stan Birchfield, Jan Kautz

End-to-end deep learning methods have advanced stereo vision in recent years and obtained excellent results when the training and test data are similar.

Level Set Stereo for Cooperative Grouping with Occlusion

1 code implementation29 Jun 2020 Jialiang Wang, Todd Zickler

We introduce an energy and level-set optimizer that improves boundaries by encoding the essential geometry of occlusions: The spatial extent of an occlusion must equal the amplitude of the disparity jump that causes it.

Occlusion Handling

Architecture Selection via the Trade-off Between Accuracy and Robustness

no code implementations4 Jun 2019 Zhun Deng, Cynthia Dwork, Jialiang Wang, Yao Zhao

We provide a general framework for characterizing the trade-off between accuracy and robustness in supervised learning.

Adversarial Attack

Local Detection of Stereo Occlusion Boundaries

no code implementations CVPR 2019 Jialiang Wang, Todd Zickler

Stereo occlusion boundaries are one-dimensional structures in the visual field that separate foreground regions of a scene that are visible to both eyes (binocular regions) from background regions of a scene that are visible to only one eye (monocular regions).

Stereo Matching Stereo Matching Hand

Toward Perceptually-Consistent Stereo: A Scanline Study

no code implementations ICCV 2017 Jialiang Wang, Daniel Glasner, Todd Zickler

Two types of information exist in a stereo pair: correlation (matching) and decorrelation (half-occlusion).

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