Search Results for author: Junru Wu

Found 15 papers, 8 papers with code

Scaling Multimodal Pre-Training via Cross-Modality Gradient Harmonization

no code implementations3 Nov 2022 Junru Wu, Yi Liang, Feng Han, Hassan Akbari, Zhangyang Wang, Cong Yu

For example, even in the commonly adopted instructional videos, a speaker can sometimes refer to something that is not visually present in the current frame; and the semantic misalignment would only be more unpredictable for the raw videos from the internet.

Contrastive Learning

Grasping the Arrow of Time from the Singularity: Decoding Micromotion in Low-dimensional Latent Spaces from StyleGAN

1 code implementation27 Apr 2022 Qiucheng Wu, Yifan Jiang, Junru Wu, Kai Wang, Gong Zhang, Humphrey Shi, Zhangyang Wang, Shiyu Chang

To study the motion features in the latent space of StyleGAN, in this paper, we hypothesize and demonstrate that a series of meaningful, natural, and versatile small, local movements (referred to as "micromotion", such as expression, head movement, and aging effect) can be represented in low-rank spaces extracted from the latent space of a conventionally pre-trained StyleGAN-v2 model for face generation, with the guidance of proper "anchors" in the form of either short text or video clips.

Disentanglement Face Generation

Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics

1 code implementation26 Aug 2021 Wuyang Chen, Xinyu Gong, Junru Wu, Yunchao Wei, Humphrey Shi, Zhicheng Yan, Yi Yang, Zhangyang Wang

This work targets designing a principled and unified training-free framework for Neural Architecture Search (NAS), with high performance, low cost, and in-depth interpretation.

Neural Architecture Search

Stronger NAS with Weaker Predictors

1 code implementation NeurIPS 2021 Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang Wang, Zicheng Liu, Mei Chen, Lu Yuan

We propose a paradigm shift from fitting the whole architecture space using one strong predictor, to progressively fitting a search path towards the high-performance sub-space through a set of weaker predictors.

Neural Architecture Search

Weak NAS Predictor Is All You Need

no code implementations1 Jan 2021 Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang Wang, Zicheng Liu, Mei Chen, Lu Yuan

Rather than expecting a single strong predictor to model the whole space, we seek a progressive line of weak predictors that can connect a path to the best architecture, thus greatly simplifying the learning task of each predictor.

Neural Architecture Search

DAVID: Dual-Attentional Video Deblurring

no code implementations7 Dec 2019 Junru Wu, Xiang Yu, Ding Liu, Manmohan Chandraker, Zhangyang Wang

To train and evaluate on more diverse blur severity levels, we propose a Challenging DVD dataset generated from the raw DVD video set by pooling frames with different temporal windows.

Deblurring

DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better

6 code implementations ICCV 2019 Orest Kupyn, Tetiana Martyniuk, Junru Wu, Zhangyang Wang

We present a new end-to-end generative adversarial network (GAN) for single image motion deblurring, named DeblurGAN-v2, which considerably boosts state-of-the-art deblurring efficiency, quality, and flexibility.

Blind Face Restoration Image Deblurring +3

Segmentation-Aware Image Denoising without Knowing True Segmentation

2 code implementations22 May 2019 Sicheng Wang, Bihan Wen, Junru Wu, DaCheng Tao, Zhangyang Wang

Several recent works discussed application-driven image restoration neural networks, which are capable of not only removing noise in images but also preserving their semantic-aware details, making them suitable for various high-level computer vision tasks as the pre-processing step.

Image Denoising Image Restoration +1

Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions

1 code implementation ICML 2018 Junru Wu, Yue Wang, Zhen-Yu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin

The current trend of pushing CNNs deeper with convolutions has created a pressing demand to achieve higher compression gains on CNNs where convolutions dominate the computation and parameter amount (e. g., GoogLeNet, ResNet and Wide ResNet).

Deep $k$-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions

1 code implementation24 Jun 2018 Junru Wu, Yue Wang, Zhen-Yu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin

The current trend of pushing CNNs deeper with convolutions has created a pressing demand to achieve higher compression gains on CNNs where convolutions dominate the computation and parameter amount (e. g., GoogLeNet, ResNet and Wide ResNet).

Gaze Prediction in Dynamic 360° Immersive Videos

no code implementations CVPR 2018 Yanyu Xu, Yanbing Dong, Junru Wu, Zhengzhong Sun, Zhiru Shi, Jingyi Yu, Shenghua Gao

This paper explores gaze prediction in dynamic $360^circ$ immersive videos, emph{i. e.}, based on the history scan path and VR contents, we predict where a viewer will look at an upcoming time.

Gaze Prediction

Personalized Saliency and its Prediction

1 code implementation9 Oct 2017 Yanyu Xu, Shenghua Gao, Junru Wu, Nianyi Li, Jingyi Yu

Specifically, we propose to decompose a personalized saliency map (referred to as PSM) into a universal saliency map (referred to as USM) predictable by existing saliency detection models and a new discrepancy map across users that characterizes personalized saliency.

Saliency Detection

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