no code implementations • 29 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.
1 code implementation • 19 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.
1 code implementation • 27 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.
no code implementations • 29 Dec 2023 • Feng Liang, Bichen Wu, Jialiang Wang, Licheng Yu, Kunpeng Li, Yinan Zhao, Ishan Misra, Jia-Bin Huang, Peizhao Zhang, Peter Vajda, Diana Marculescu
This enables our model for video synthesis by editing the first frame with any prevalent I2I models and then propagating edits to successive frames.
no code implementations • 9 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.
no code implementations • 8 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.
no code implementations • 6 Dec 2023 • Felix Wimbauer, Bichen Wu, Edgar Schoenfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam Tsai, Jonas Kohler, Christian Rupprecht, Daniel Cremers, Peter Vajda, Jialiang Wang
However, one of the major drawbacks of diffusion models is that the image generation process is costly.
no code implementations • 27 Sep 2023 • Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, Matthew Yu, Abhishek Kadian, Filip Radenovic, Dhruv Mahajan, Kunpeng Li, Yue Zhao, Vladan Petrovic, Mitesh Kumar Singh, Simran Motwani, Yi Wen, Yiwen Song, Roshan Sumbaly, Vignesh Ramanathan, Zijian He, Peter Vajda, Devi Parikh
Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text.
2 code implementations • ICCV 2023 • Chenfeng Xu, Bichen Wu, Ji Hou, Sam Tsai, RuiLong Li, Jialiang Wang, Wei Zhan, Zijian He, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka
We present NeRF-Det, a novel method for indoor 3D detection with posed RGB images as input.
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.
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.
no code implementations • 12 Aug 2022 • Jialiang Wang, Yurong Zhong, Weiling Li
Determining these hyperparameters is time-consuming and it largely reduces the practicability of an SLF model.
no code implementations • 24 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.
1 code implementation • CVPR 2022 • Cho-Ying Wu, Jialiang Wang, Michael Hall, Ulrich Neumann, Shuochen Su
The majority of prior monocular depth estimation methods without groundtruth depth guidance focus on driving scenarios.
Ranked #1 on Monocular Depth Estimation on VA (Virtual Apartment)
no code implementations • 19 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.
Ranked #7 on Neural Architecture Search on ImageNet
1 code implementation • 8 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.
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.
no code implementations • 25 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.
1 code implementation • 29 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.
no code implementations • 4 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.
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).
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).