Search Results for author: Jian Ren

Found 20 papers, 8 papers with code

Are Multimodal Transformers Robust to Missing Modality?

no code implementations12 Apr 2022 Mengmeng Ma, Jian Ren, Long Zhao, Davide Testuggine, Xi Peng

Based on these findings, we propose a principle method to improve the robustness of Transformer models by automatically searching for an optimal fusion strategy regarding input data.

R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis

1 code implementation31 Mar 2022 Huan Wang, Jian Ren, Zeng Huang, Kyle Olszewski, Menglei Chai, Yun Fu, Sergey Tulyakov

On the other hand, Neural Light Field (NeLF) presents a more straightforward representation over NeRF in novel view synthesis -- the rendering of a pixel amounts to one single forward pass without ray-marching.

Novel View Synthesis

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

1 code implementation4 Mar 2022 Ligong Han, Jian Ren, Hsin-Ying Lee, Francesco Barbieri, Kyle Olszewski, Shervin Minaee, Dimitris Metaxas, Sergey Tulyakov

In addition, our model can extract visual information as suggested by the text prompt, e. g., "an object in image one is moving northeast", and generate corresponding videos.

Self-Learning Text Augmentation +1

F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

1 code implementation ICLR 2022 Qing Jin, Jian Ren, Richard Zhuang, Sumant Hanumante, Zhengang Li, Zhiyu Chen, Yanzhi Wang, Kaiyuan Yang, Sergey Tulyakov

Our approach achieves comparable and better performance, when compared not only to existing quantization techniques with INT32 multiplication or floating-point arithmetic, but also to the full-precision counterparts, achieving state-of-the-art performance.

Quantization

A Critical Analysis of Image-based Camera Pose Estimation Techniques

no code implementations15 Jan 2022 Meng Xu, Youchen Wang, Bin Xu, Jun Zhang, Jian Ren, Stefan Poslad, Pengfei Xu

Camera, and associated with its objects within the field of view, localization could benefit many computer vision fields, such as autonomous driving, robot navigation, and augmented reality (AR).

Autonomous Driving Camera Localization +2

PIM-QAT: Neural Network Quantization For Processing-In-Memory (PIM) Systems

no code implementations29 Sep 2021 Qing Jin, Zhiyu Chen, Jian Ren, Yanyu Li, Yanzhi Wang, Kaiyuan Yang

However, an extra quantization step (i. e. PIM quantization), typically with limited resolution due to hardware constraints, is required to convert the analog computing results into digital domain.

Quantization

BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection

1 code implementation18 Jun 2021 Yulin Zhu, Yuni Lai, Kaifa Zhao, Xiapu Luo, Mingquan Yuan, Jian Ren, Kai Zhou

Graph-based Anomaly Detection (GAD) is becoming prevalent due to the powerful representation abilities of graphs as well as recent advances in graph mining techniques.

Anomaly Detection Combinatorial Optimization +2

Motion Representations for Articulated Animation

2 code implementations CVPR 2021 Aliaksandr Siarohin, Oliver J. Woodford, Jian Ren, Menglei Chai, Sergey Tulyakov

To facilitate animation and prevent the leakage of the shape of the driving object, we disentangle shape and pose of objects in the region space.

Video Reconstruction

In&Out : Diverse Image Outpainting via GAN Inversion

no code implementations1 Apr 2021 Yen-Chi Cheng, Chieh Hubert Lin, Hsin-Ying Lee, Jian Ren, Sergey Tulyakov, Ming-Hsuan Yang

Existing image outpainting methods pose the problem as a conditional image-to-image translation task, often generating repetitive structures and textures by replicating the content available in the input image.

Image Outpainting Image-to-Image Translation +1

SMIL: Multimodal Learning with Severely Missing Modality

1 code implementation9 Mar 2021 Mengmeng Ma, Jian Ren, Long Zhao, Sergey Tulyakov, Cathy Wu, Xi Peng

A common assumption in multimodal learning is the completeness of training data, i. e., full modalities are available in all training examples.

Meta-Learning

Teachers Do More Than Teach: Compressing Image-to-Image Models

1 code implementation CVPR 2021 Qing Jin, Jian Ren, Oliver J. Woodford, Jiazhuo Wang, Geng Yuan, Yanzhi Wang, Sergey Tulyakov

In this work, we aim to address these issues by introducing a teacher network that provides a search space in which efficient network architectures can be found, in addition to performing knowledge distillation.

Knowledge Distillation

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?

no code implementations19 Feb 2021 Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang

In deep model compression, the recent finding "Lottery Ticket Hypothesis" (LTH) (Frankle & Carbin, 2018) pointed out that there could exist a winning ticket (i. e., a properly pruned sub-network together with original weight initialization) that can achieve competitive performance than the original dense network.

Model Compression

Neural Hair Rendering

no code implementations ECCV 2020 Menglei Chai, Jian Ren, Sergey Tulyakov

Unlike existing supervised translation methods that require model-level similarity to preserve consistent structure representation for both real images and fake renderings, our method adopts an unsupervised solution to work on arbitrary hair models.

Translation

Human Motion Transfer from Poses in the Wild

no code implementations7 Apr 2020 Jian Ren, Menglei Chai, Sergey Tulyakov, Chen Fang, Xiaohui Shen, Jianchao Yang

In this paper, we tackle the problem of human motion transfer, where we synthesize novel motion video for a target person that imitates the movement from a reference video.

Translation

EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching from Scratch

no code implementations CVPR 2019 Jian Ren, Zhe Li, Jianchao Yang, Ning Xu, Tianbao Yang, David J. Foran

In this paper, we propose an Ecologically-Inspired GENetic (EIGEN) approach that uses the concept of succession, extinction, mimicry, and gene duplication to search neural network structure from scratch with poorly initialized simple network and few constraints forced during the evolution, as we assume no prior knowledge about the task domain.

Factorized Adversarial Networks for Unsupervised Domain Adaptation

no code implementations4 Jun 2018 Jian Ren, Jianchao Yang, Ning Xu, David J. Foran

In this paper, we propose Factorized Adversarial Networks (FAN) to solve unsupervised domain adaptation problems for image classification tasks.

General Classification Image Classification +1

Personalized Image Aesthetics

no code implementations ICCV 2017 Jian Ren, Xiaohui Shen, Zhe Lin, Radomir Mech, David J. Foran

To accommodate our study, we first collect two distinct datasets, a large image dataset from Flickr and annotated by Amazon Mechanical Turk, and a small dataset of real personal albums rated by owners.

Active Learning

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