Search Results for author: Chang Chen

Found 30 papers, 11 papers with code

Simple Hierarchical Planning with Diffusion

no code implementations5 Jan 2024 Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn

Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets.

Computational Spectral Imaging with Unified Encoding Model: A Comparative Study and Beyond

no code implementations20 Dec 2023 Xinyuan Liu, Lizhi Wang, Lingen Li, Chang Chen, Xue Hu, Fenglong Song, Youliang Yan

Computational spectral imaging is drawing increasing attention owing to the snapshot advantage, and amplitude, phase, and wavelength encoding systems are three types of representative implementations.


All Languages Matter: On the Multilingual Safety of Large Language Models

1 code implementation2 Oct 2023 Wenxuan Wang, Zhaopeng Tu, Chang Chen, Youliang Yuan, Jen-tse Huang, Wenxiang Jiao, Michael R. Lyu

In this work, we build the first multilingual safety benchmark for LLMs, XSafety, in response to the global deployment of LLMs in practice.

An Image is Worth a Thousand Toxic Words: A Metamorphic Testing Framework for Content Moderation Software

no code implementations18 Aug 2023 Wenxuan Wang, Jingyuan Huang, Jen-tse Huang, Chang Chen, Jiazhen Gu, Pinjia He, Michael R. Lyu

Moreover, through retraining the models with the test cases generated by OASIS, the robustness of the moderation model can be improved without performance degradation.

Validating Multimedia Content Moderation Software via Semantic Fusion

no code implementations23 May 2023 Wenxuan Wang, Jingyuan Huang, Chang Chen, Jiazhen Gu, Jianping Zhang, Weibin Wu, Pinjia He, Michael Lyu

To this end, content moderation software has been widely deployed on these platforms to detect and blocks toxic content.


Toward DNN of LUTs: Learning Efficient Image Restoration with Multiple Look-Up Tables

1 code implementation25 Mar 2023 Jiacheng Li, Chang Chen, Zhen Cheng, Zhiwei Xiong

However, the size of a single LUT grows exponentially with the increase of its indexing capacity, which restricts its receptive field and thus the performance.

Demosaicking Denoising +1

TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training

1 code implementation20 Feb 2023 Chang Chen, Min Li, Zhihua Wu, dianhai yu, Chao Yang

In this paper, we propose TA-MoE, a topology-aware routing strategy for large-scale MoE trainging, from a model-system co-design perspective, which can dynamically adjust the MoE dispatch pattern according to the network topology.

Toward RAW Object Detection: A New Benchmark and a New Model

no code implementations CVPR 2023 Ruikang Xu, Chang Chen, Jingyang Peng, Cheng Li, Yibin Huang, Fenglong Song, Youliang Yan, Zhiwei Xiong

In many computer vision applications (e. g., robotics and autonomous driving), high dynamic range (HDR) data is necessary for object detection algorithms to handle a variety of lighting conditions, such as strong glare.

Autonomous Driving Object +2

Style Projected Clustering for Domain Generalized Semantic Segmentation

no code implementations CVPR 2023 Wei Huang, Chang Chen, Yong Li, Jiacheng Li, Cheng Li, Fenglong Song, Youliang Yan, Zhiwei Xiong

In contrast to existing methods, we instead utilize the difference between images to build a better representation space, where the distinct style features are extracted and stored as the bases of representation.

Clustering Semantic Segmentation

GARF:Geometry-Aware Generalized Neural Radiance Field

no code implementations5 Dec 2022 Yue Shi, Dingyi Rong, Bingbing Ni, Chang Chen, Wenjun Zhang

To address these issues, we propose Geometry-Aware Generalized Neural Radiance Field (GARF) with a geometry-aware dynamic sampling (GADS) strategy to perform real-time novel view rendering and unsupervised depth estimation on unseen scenes without per-scene optimization.

Decoder Depth Estimation +2

Towards Real World HDRTV Reconstruction: A Data Synthesis-based Approach

no code implementations6 Nov 2022 Zhen Cheng, Tao Wang, Yong Li, Fenglong Song, Chang Chen, Zhiwei Xiong

To solve this problem, we propose a learning-based data synthesis approach to learn the properties of real-world SDRTVs by integrating several tone mapping priors into both network structures and loss functions.

Tone Mapping

Trans4Map: Revisiting Holistic Bird's-Eye-View Mapping from Egocentric Images to Allocentric Semantics with Vision Transformers

1 code implementation13 Jul 2022 Chang Chen, Jiaming Zhang, Kailun Yang, Kunyu Peng, Rainer Stiefelhagen

Humans have an innate ability to sense their surroundings, as they can extract the spatial representation from the egocentric perception and form an allocentric semantic map via spatial transformation and memory updating.

Decoder Semantic Segmentation

TransDreamer: Reinforcement Learning with Transformer World Models

no code implementations19 Feb 2022 Chang Chen, Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn

We then share this world model with a transformer-based policy network and obtain stability in training a transformer-based RL agent.

Model-based Reinforcement Learning reinforcement-learning +1

Retinal Vessel Segmentation with Pixel-wise Adaptive Filters

1 code implementation3 Feb 2022 Mingxing Li, Shenglong Zhou, Chang Chen, Yueyi Zhang, Dong Liu, Zhiwei Xiong

Accurate retinal vessel segmentation is challenging because of the complex texture of retinal vessels and low imaging contrast.

Retinal Vessel Segmentation Segmentation

Contextual Outpainting With Object-Level Contrastive Learning

no code implementations CVPR 2022 Jiacheng Li, Chang Chen, Zhiwei Xiong

To model the contextual correlation between foreground and background contents, we incorporate an object-level contrastive loss to regularize the learning of cross-modal representations of foreground contents and the corresponding background semantic layout, facilitating accurate semantic reasoning.

Contrastive Learning Image Outpainting +1

Continuous Spectral Reconstruction from RGB Images via Implicit Neural Representation

no code implementations24 Dec 2021 Ruikang Xu, Mingde Yao, Chang Chen, Lizhi Wang, Zhiwei Xiong

In this paper, we propose Neural Spectral Reconstruction (NeSR) to lift this limitation, by introducing a novel continuous spectral representation.

Spectral Reconstruction

Light Field Super-Resolution With Zero-Shot Learning

no code implementations CVPR 2021 Zhen Cheng, Zhiwei Xiong, Chang Chen, Dong Liu, Zheng-Jun Zha

To fill this gap, we propose a zero-shot learning framework for light field SR, which learns a mapping to super-resolve the reference view with examples extracted solely from the input low-resolution light field itself.

Super-Resolution Zero-Shot Learning

Advanced Deep Networks for 3D Mitochondria Instance Segmentation

1 code implementation16 Apr 2021 Mingxing Li, Chang Chen, Xiaoyu Liu, Wei Huang, Yueyi Zhang, Zhiwei Xiong

Mitochondria instance segmentation from electron microscopy (EM) images has seen notable progress since the introduction of deep learning methods.

3D Instance Segmentation Denoising +2

Learning the Evolution of the Universe in N-body Simulations

no code implementations10 Dec 2020 Chang Chen, Yin Li, Francisco Villaescusa-Navarro, Shirley Ho, Anthony Pullen

Understanding the physics of large cosmological surveys down to small (nonlinear) scales will significantly improve our knowledge of the Universe.

Hierarchical Classification of Pulmonary Lesions: A Large-Scale Radio-Pathomics Study

no code implementations8 Oct 2020 Jiancheng Yang, Mingze Gao, Kaiming Kuang, Bingbing Ni, Yunlang She, Dong Xie, Chang Chen

A three-level hierarchical classification system for pulmonary lesions is developed, which covers most diseases in cancer-related diagnosis.

Computed Tomography (CT) Decision Making +2

ROOTS: Object-Centric Representation and Rendering of 3D Scenes

no code implementations11 Jun 2020 Chang Chen, Fei Deng, Sungjin Ahn

A crucial ability of human intelligence is to build up models of individual 3D objects from partial scene observations.

Object Representation Learning +1

Camera Trace Erasing

1 code implementation CVPR 2020 Chang Chen, Zhiwei Xiong, Xiaoming Liu, Feng Wu

To reconcile these two demands, we propose Siamese Trace Erasing (SiamTE), in which a novel hybrid loss is designed on the basis of Siamese architecture for network training.


no code implementations25 Sep 2019 Chang Chen, Sungjin Ahn

In this paper, we propose a generative model, called ROOTS (Representation of Object-Oriented Three-dimension Scenes), for unsupervised object-wise 3D-scene decomposition and and rendering.

Disentanglement Object

Camera Lens Super-Resolution

1 code implementation CVPR 2019 Chang Chen, Zhiwei Xiong, Xinmei Tian, Zheng-Jun Zha, Feng Wu

Existing methods for single image super-resolution (SR) are typically evaluated with synthetic degradation models such as bicubic or Gaussian downsampling.

Image Super-Resolution

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