Search Results for author: Zhenhong Sun

Found 12 papers, 8 papers with code

Learning Accurate Entropy Model with Global Reference for Image Compression

2 code implementations ICLR 2021 Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin

In this work, we propose a novel Global Reference Model for image compression to effectively leverage both the local and the global context information, leading to an enhanced compression rate.

Image Compression

Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition

2 code implementations ICCV 2021 Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin

To address this issue, instead of using an accuracy predictor, we propose a novel zero-shot index dubbed Zen-Score to rank the architectures.

Neural Architecture Search Vocal Bursts Intensity Prediction

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

2 code implementations1 Feb 2021 Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin

Comparing with previous NAS methods, the proposed Zen-NAS is magnitude times faster on multiple server-side and mobile-side GPU platforms with state-of-the-art accuracy on ImageNet.

Image Classification Neural Architecture Search

Spatiotemporal Entropy Model is All You Need for Learned Video Compression

1 code implementation13 Apr 2021 Zhenhong Sun, Zhiyu Tan, Xiuyu Sun, Fangyi Zhang, Dongyang Li, Yichen Qian, Hao Li

The framework of dominant learned video compression methods is usually composed of motion prediction modules as well as motion vector and residual image compression modules, suffering from its complex structure and error propagation problem.

Image Compression motion prediction +3

Interpolation variable rate image compression

1 code implementation20 Sep 2021 Zhenhong Sun, Zhiyu Tan, Xiuyu Sun, Fangyi Zhang, Yichen Qian, Dongyang Li, Hao Li

Compression standards have been used to reduce the cost of image storage and transmission for decades.

Image Compression MS-SSIM +1

ZenDet: Revisiting Efficient Object Detection Backbones from Zero-Shot Neural Architecture Search

no code implementations29 Sep 2021 Zhenhong Sun, Ming Lin, Zhiyu Tan, Xiuyu Sun, Rong Jin

Recent researches attempt to reduce this cost by optimizing the backbone architecture with the help of Neural Architecture Search (NAS).

Neural Architecture Search Object +2

MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection

1 code implementation26 Nov 2021 Zhenhong Sun, Ming Lin, Xiuyu Sun, Zhiyu Tan, Hao Li, Rong Jin

Recent researches attempt to reduce this cost by optimizing the backbone architecture with the help of Neural Architecture Search (NAS).

Neural Architecture Search Object +2

Entropy-Driven Mixed-Precision Quantization for Deep Network Design

1 code implementation Conference on Neural Information Processing Systems 2022 Zhenhong Sun, Ce Ge, Junyan Wang, Ming Lin, Hesen Chen, Hao Li, Xiuyu Sun

Deploying deep convolutional neural networks on Internet-of-Things (IoT) devices is challenging due to the limited computational resources, such as limited SRAM memory and Flash storage.

Face Detection Hardware Aware Neural Architecture Search +3

Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition

1 code implementation5 Mar 2023 Junyan Wang, Zhenhong Sun, Yichen Qian, Dong Gong, Xiuyu Sun, Ming Lin, Maurice Pagnucco, Yang song

In this work, we propose to automatically design efficient 3D CNN architectures via a novel training-free neural architecture search approach tailored for 3D CNNs considering the model complexity.

Action Recognition Computational Efficiency +2

Tomography of Quantum States from Structured Measurements via quantum-aware transformer

no code implementations9 May 2023 Hailan Ma, Zhenhong Sun, Daoyi Dong, Chunlin Chen, Herschel Rabitz

Quantum state tomography (QST) is the process of reconstructing the state of a quantum system (mathematically described as a density matrix) through a series of different measurements, which can be solved by learning a parameterized function to translate experimentally measured statistics into physical density matrices.

Language Modelling Quantum State Tomography

Learning Informative Latent Representation for Quantum State Tomography

no code implementations30 Sep 2023 Hailan Ma, Zhenhong Sun, Daoyi Dong, Dong Gong

Our method leverages a transformer-based encoder to extract an informative latent representation (ILR) from imperfect measurement data and employs a decoder to predict the quantum states based on the ILR.

Quantum State Tomography

Towards Effective Usage of Human-Centric Priors in Diffusion Models for Text-based Human Image Generation

no code implementations8 Mar 2024 Junyan Wang, Zhenhong Sun, Zhiyu Tan, Xuanbai Chen, Weihua Chen, Hao Li, Cheng Zhang, Yang song

Vanilla text-to-image diffusion models struggle with generating accurate human images, commonly resulting in imperfect anatomies such as unnatural postures or disproportionate limbs. Existing methods address this issue mostly by fine-tuning the model with extra images or adding additional controls -- human-centric priors such as pose or depth maps -- during the image generation phase.

Image Generation

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