Search Results for author: Ze Yang

Found 29 papers, 11 papers with code

LightSim: Neural Lighting Simulation for Urban Scenes

no code implementations11 Dec 2023 Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun

Different outdoor illumination conditions drastically alter the appearance of urban scenes, and they can harm the performance of image-based robot perception systems if not seen during training.

Reconstructing Objects in-the-wild for Realistic Sensor Simulation

no code implementations9 Nov 2023 Ze Yang, Sivabalan Manivasagam, Yun Chen, Jingkang Wang, Rui Hu, Raquel Urtasun

In this work, we present NeuSim, a novel approach that estimates accurate geometry and realistic appearance from sparse in-the-wild data captured at distance and at limited viewpoints.

CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation

no code implementations2 Nov 2023 Jingkang Wang, Sivabalan Manivasagam, Yun Chen, Ze Yang, Ioan Andrei Bârsan, Anqi Joyce Yang, Wei-Chiu Ma, Raquel Urtasun

To tackle these issues, we present CADSim, which combines part-aware object-class priors via a small set of CAD models with differentiable rendering to automatically reconstruct vehicle geometry, including articulated wheels, with high-quality appearance.

3D Reconstruction

UniSim: A Neural Closed-Loop Sensor Simulator

2 code implementations CVPR 2023 Ze Yang, Yun Chen, Jingkang Wang, Sivabalan Manivasagam, Wei-Chiu Ma, Anqi Joyce Yang, Raquel Urtasun

Previously recorded driving logs provide a rich resource to build these new scenarios from, but for closed loop evaluation, we need to modify the sensor data based on the new scene configuration and the SDV's decisions, as actors might be added or removed and the trajectories of existing actors and the SDV will differ from the original log.

Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing

no code implementations ICCV 2023 Sivabalan Manivasagam, Ioan Andrei Bârsan, Jingkang Wang, Ze Yang, Raquel Urtasun

We leverage this setting to analyze what aspects of LiDAR simulation, such as pulse phenomena, scanning effects, and asset quality, affect the domain gap with respect to the autonomy system, including perception, prediction, and motion planning, and analyze how modifications to the simulated LiDAR influence each part.

Motion Planning

Label-Guided Knowledge Distillation for Continual Semantic Segmentation on 2D Images and 3D Point Clouds

1 code implementation ICCV 2023 Ze Yang, Ruibo Li, Evan Ling, Chi Zhang, Yiming Wang, Dezhao Huang, Keng Teck Ma, Minhoe Hur, Guosheng Lin

To address this issue, we propose a new label-guided knowledge distillation (LGKD) loss, where the old model output is expanded and transplanted (with the guidance of the ground truth label) to form a semantically appropriate class correspondence with the new model output.

Continual Semantic Segmentation Knowledge Distillation +1

TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization

no code implementations Findings (NAACL) 2022 Ze Yang, Liran Wang, Zhoujin Tian, Wei Wu, Zhoujun Li

Another is that applying the existing pre-trained models to this task is tricky because of the structural dependence within the conversation and its informal expression, etc.

RBGNet: Ray-based Grouping for 3D Object Detection

1 code implementation CVPR 2022 Haiyang Wang, Shaoshuai Shi, Ze Yang, Rongyao Fang, Qi Qian, Hongsheng Li, Bernt Schiele, LiWei Wang

In order to learn better representations of object shape to enhance cluster features for predicting 3D boxes, we propose a ray-based feature grouping module, which aggregates the point-wise features on object surfaces using a group of determined rays uniformly emitted from cluster centers.

3D Object Detection Object +1

Efficient Few-Shot Object Detection via Knowledge Inheritance

1 code implementation23 Mar 2022 Ze Yang, Chi Zhang, Ruibo Li, Yi Xu, Guosheng Lin

Upon this baseline, we devise an initializer named knowledge inheritance (KI) to reliably initialize the novel weights for the box classifier, which effectively facilitates the knowledge transfer process and boosts the adaptation speed.

Few-Shot Object Detection Object +2

Assessment of Deep Learning-based Heart Rate Estimation using Remote Photoplethysmography under Different Illuminations

no code implementations28 Jul 2021 Ze Yang, Haofei Wang, Feng Lu

We evaluate the performance of three deep learning-based methods (Deepphys, rPPGNet, and Physnet) to that of four traditional methods (CHROM, GREEN, ICA, and POS) using two public datasets: the UBFC-rPPG dataset and the BH-rPPG dataset.

Heart rate estimation POS

S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling

no code implementations CVPR 2021 Ze Yang, Shenlong Wang, Sivabalan Manivasagam, Zeng Huang, Wei-Chiu Ma, Xinchen Yan, Ersin Yumer, Raquel Urtasun

Constructing and animating humans is an important component for building virtual worlds in a wide variety of applications such as virtual reality or robotics testing in simulation.

Recovering and Simulating Pedestrians in the Wild

no code implementations16 Nov 2020 Ze Yang, Siva Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun

We then incorporate the reconstructed pedestrian assets bank in a realistic LiDAR simulation system by performing motion retargeting, and show that the simulated LiDAR data can be used to significantly reduce the amount of annotated real-world data required for visual perception tasks.

Data Augmentation motion retargeting

StyleDGPT: Stylized Response Generation with Pre-trained Language Models

1 code implementation Findings of the Association for Computational Linguistics 2020 Ze Yang, Wei Wu, Can Xu, Xinnian Liang, Jiaqi Bai, Liran Wang, Wei Wang, Zhoujun Li

Generating responses following a desired style has great potentials to extend applications of open-domain dialogue systems, yet is refrained by lacking of parallel data for training.

Response Generation Sentence

Open Domain Dialogue Generation with Latent Images

no code implementations4 Apr 2020 Ze Yang, Wei Wu, Huang Hu, Can Xu, Wei Wang, Zhoujun Li

Thus, we propose learning a response generation model with both image-grounded dialogues and textual dialogues by assuming that the visual scene information at the time of a conversation can be represented by an image, and trying to recover the latent images of the textual dialogues through text-to-image generation techniques.

Dialogue Generation Response Generation +1

Context-Transformer: Tackling Object Confusion for Few-Shot Detection

1 code implementation16 Mar 2020 Ze Yang, Yali Wang, Xianyu Chen, Jianzhuang Liu, Yu Qiao

Few-shot object detection is a challenging but realistic scenario, where only a few annotated training images are available for training detectors.

Few-Shot Learning Few-Shot Object Detection +3

Dense RepPoints: Representing Visual Objects with Dense Point Sets

2 code implementations ECCV 2020 Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Li-Wei Wang, Stephen Lin, Han Hu

We present a new object representation, called Dense RepPoints, that utilizes a large set of points to describe an object at multiple levels, including both box level and pixel level.

Object Object Detection

Model Compression with Two-stage Multi-teacher Knowledge Distillation for Web Question Answering System

no code implementations18 Oct 2019 Ze Yang, Linjun Shou, Ming Gong, Wutao Lin, Daxin Jiang

The experiment results show that our method can significantly outperform the baseline methods and even achieve comparable results with the original teacher models, along with substantial speedup of model inference.

General Knowledge Knowledge Distillation +3

Learning Relationships for Multi-View 3D Object Recognition

no code implementations ICCV 2019 Ze Yang, Liwei Wang

Recognizing 3D object has attracted plenty of attention recently, and view-based methods have achieved best results until now.

3D Object Recognition Object +3

On the Anomalous Generalization of GANs

no code implementations27 Sep 2019 Jinchen Xuan, Yunchang Yang, Ze Yang, Di He, Li-Wei Wang

Motivated by this observation, we discover two specific problems of GANs leading to anomalous generalization behaviour, which we refer to as the sample insufficiency and the pixel-wise combination.

Low-Resource Response Generation with Template Prior

1 code implementation IJCNLP 2019 Ze Yang, Wei Wu, Jian Yang, Can Xu, Zhoujun Li

Since the paired data now is no longer enough to train a neural generation model, we consider leveraging the large scale of unpaired data that are much easier to obtain, and propose response generation with both paired and unpaired data.

Decoder Response Generation

Model Compression with Multi-Task Knowledge Distillation for Web-scale Question Answering System

no code implementations21 Apr 2019 Ze Yang, Linjun Shou, Ming Gong, Wutao Lin, Daxin Jiang

Deep pre-training and fine-tuning models (like BERT, OpenAI GPT) have demonstrated excellent results in question answering areas.

Knowledge Distillation Model Compression +1

NeuronBlocks: Building Your NLP DNN Models Like Playing Lego

2 code implementations IJCNLP 2019 Ming Gong, Linjun Shou, Wutao Lin, Zhijie Sang, Quanjia Yan, Ze Yang, Feixiang Cheng, Daxin Jiang

Deep Neural Networks (DNN) have been widely employed in industry to address various Natural Language Processing (NLP) tasks.

Learning to Navigate for Fine-grained Classification

12 code implementations ECCV 2018 Ze Yang, Tiange Luo, Dong Wang, Zhiqiang Hu, Jun Gao, Li-Wei Wang

In consideration of intrinsic consistency between informativeness of the regions and their probability being ground-truth class, we design a novel training paradigm, which enables Navigator to detect most informative regions under the guidance from Teacher.

Fine-Grained Image Classification General Classification +1

Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network

no code implementations23 Mar 2017 Yudong Liang, Ze Yang, Kai Zhang, Yihui He, Jinjun Wang, Nanning Zheng

To tackle with the second problem, a lightweight CNN architecture which has carefully designed width, depth and skip connections was proposed.

Image Super-Resolution SSIM

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