Search Results for author: Yingya Zhang

Found 21 papers, 11 papers with code

Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning

1 code implementation14 Sep 2023 Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yingya Zhang, Changxin Gao, Deli Zhao, Nong Sang

When pre-training on the large-scale Kinetics-710, we achieve 89. 7% on Kinetics-400 with a frozen ViT-L model, which verifies the scalability of DiST.

Transfer Learning Video Recognition

RLIPv2: Fast Scaling of Relational Language-Image Pre-training

2 code implementations18 Aug 2023 Hangjie Yuan, Shiwei Zhang, Xiang Wang, Samuel Albanie, Yining Pan, Tao Feng, Jianwen Jiang, Dong Ni, Yingya Zhang, Deli Zhao

In this paper, we propose RLIPv2, a fast converging model that enables the scaling of relational pre-training to large-scale pseudo-labelled scene graph data.

 Ranked #1 on Zero-Shot Human-Object Interaction Detection on HICO-DET (using extra training data)

Graph Generation Human-Object Interaction Detection +5

ModelScope Text-to-Video Technical Report

1 code implementation12 Aug 2023 Jiuniu Wang, Hangjie Yuan, Dayou Chen, Yingya Zhang, Xiang Wang, Shiwei Zhang

This paper introduces ModelScopeT2V, a text-to-video synthesis model that evolves from a text-to-image synthesis model (i. e., Stable Diffusion).

Denoising Image Generation

VideoComposer: Compositional Video Synthesis with Motion Controllability

1 code implementation3 Jun 2023 Xiang Wang, Hangjie Yuan, Shiwei Zhang, Dayou Chen, Jiuniu Wang, Yingya Zhang, Yujun Shen, Deli Zhao, Jingren Zhou

The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis.

Image Generation

MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action Recognition

1 code implementation CVPR 2023 Xiang Wang, Shiwei Zhang, Zhiwu Qing, Changxin Gao, Yingya Zhang, Deli Zhao, Nong Sang

To address these issues, we develop a Motion-augmented Long-short Contrastive Learning (MoLo) method that contains two crucial components, including a long-short contrastive objective and a motion autodecoder.

Contrastive Learning Few-Shot action recognition +1

Enlarging Instance-specific and Class-specific Information for Open-set Action Recognition

1 code implementation CVPR 2023 Jun Cen, Shiwei Zhang, Xiang Wang, Yixuan Pei, Zhiwu Qing, Yingya Zhang, Qifeng Chen

In this paper, we begin with analyzing the feature representation behavior in the open-set action recognition (OSAR) problem based on the information bottleneck (IB) theory, and propose to enlarge the instance-specific (IS) and class-specific (CS) information contained in the feature for better performance.

Open Set Action Recognition

VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

1 code implementation CVPR 2023 Zhengxiong Luo, Dayou Chen, Yingya Zhang, Yan Huang, Liang Wang, Yujun Shen, Deli Zhao, Jingren Zhou, Tieniu Tan

A diffusion probabilistic model (DPM), which constructs a forward diffusion process by gradually adding noise to data points and learns the reverse denoising process to generate new samples, has been shown to handle complex data distribution.

Denoising Image Generation +2

CLIP-guided Prototype Modulating for Few-shot Action Recognition

1 code implementation6 Mar 2023 Xiang Wang, Shiwei Zhang, Jun Cen, Changxin Gao, Yingya Zhang, Deli Zhao, Nong Sang

Learning from large-scale contrastive language-image pre-training like CLIP has shown remarkable success in a wide range of downstream tasks recently, but it is still under-explored on the challenging few-shot action recognition (FSAR) task.

Few-Shot action recognition Few Shot Action Recognition

The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition

1 code implementation8 Feb 2023 Jun Cen, Di Luan, Shiwei Zhang, Yixuan Pei, Yingya Zhang, Deli Zhao, Shaojie Shen, Qifeng Chen

Recently, Unified Open-set Recognition (UOSR) has been proposed to reject not only unknown samples but also known but wrongly classified samples, which tends to be more practical in real-world applications.

Open Set Learning

Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization

no code implementations14 Oct 2022 Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan

While (Lu and Sa, 2021) have recently provided an optimal rate for non-convex stochastic decentralized optimization with weight matrices defined over linear graphs, the optimal rate with general weight matrices remains unclear.

Communicate Then Adapt: An Effective Decentralized Adaptive Method for Deep Training

no code implementations29 Sep 2021 Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Yingya Zhang, Pan Pan, Wotao Yin

Decentralized adaptive gradient methods, in which each node averages only with its neighbors, are critical to save communication and wall-clock training time in deep learning tasks.

Communication Efficient SGD via Gradient Sampling With Bayes Prior

no code implementations CVPR 2021 Liuyihan Song, Kang Zhao, Pan Pan, Yu Liu, Yingya Zhang, Yinghui Xu, Rong Jin

Different from all of them, we regard large and small gradients selection as the exploitation and exploration of gradient information, respectively.

Image Classification object-detection +2

DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training

1 code implementation ICCV 2021 Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin

Experimental results on a variety of computer vision tasks and models demonstrate that DecentLaM promises both efficient and high-quality training.

Visual Search at Alibaba

no code implementations9 Feb 2021 Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Yingya Zhang, Xiaofeng Ren, Rong Jin

We hope visual search at Alibaba becomes more widely incorporated into today's commercial applications.

Image Retrieval

Large-Scale Visual Search with Binary Distributed Graph at Alibaba

no code implementations9 Feb 2021 Kang Zhao, Pan Pan, Yun Zheng, Yanhao Zhang, Changxu Wang, Yingya Zhang, Yinghui Xu, Rong Jin

For a deployed visual search system with several billions of online images in total, building a billion-scale offline graph in hours is essential, which is almost unachievable by most existing methods.

graph construction

Distribution Adaptive INT8 Quantization for Training CNNs

no code implementations9 Feb 2021 Kang Zhao, Sida Huang, Pan Pan, Yinghan Li, Yingya Zhang, Zhenyu Gu, Yinghui Xu

Researches have demonstrated that low bit-width (e. g., INT8) quantization can be employed to accelerate the inference process.

Image Classification object-detection +3

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