Search Results for author: Hang Zhao

Found 43 papers, 17 papers with code

Neural Dubber: Dubbing for Videos According to Scripts

no code implementations NeurIPS 2021 Chenxu Hu, Qiao Tian, Tingle Li, Yuping Wang, Yuxuan Wang, Hang Zhao

Most importantly, both qualitative and quantitative evaluations show that Neural Dubber can control the prosody of synthesized speech by the video, and generate high-fidelity speech temporally synchronized with the video.

Speech Quality

DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries

1 code implementation13 Oct 2021 Yue Wang, Vitor Guizilini, Tianyuan Zhang, Yilun Wang, Hang Zhao, Justin Solomon

This top-down approach outperforms its bottom-up counterpart in which object bounding box prediction follows per-pixel depth estimation, since it does not suffer from the compounding error introduced by a depth prediction model.

3D Object Detection Autonomous Driving +1

Learning Practically Feasible Policies for Online 3D Bin Packing

no code implementations31 Aug 2021 Hang Zhao, Chenyang Zhu, Xin Xu, Hui Huang, Kai Xu

In this problem, the items are delivered to the agent without informing the full sequence information.

3D Bin Packing

DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets

1 code implementation ICCV 2021 Junru Gu, Chen Sun, Hang Zhao

In this work, we propose an anchor-free and end-to-end trajectory prediction model, named DenseTNT, that directly outputs a set of trajectories from dense goal candidates.

Motion Forecasting motion prediction +1

HDMapNet: A Local Semantic Map Learning and Evaluation Framework

1 code implementation13 Jul 2021 Qi Li, Yue Wang, Yilun Wang, Hang Zhao

By introducing the method and metrics, we invite the community to study this novel map learning problem.

Autonomous Driving

DenseTNT: Waymo Open Dataset Motion Prediction Challenge 1st Place Solution

1 code implementation27 Jun 2021 Junru Gu, Qiao Sun, Hang Zhao

In autonomous driving, goal-based multi-trajectory prediction methods are proved to be effective recently, where they first score goal candidates, then select a final set of goals, and finally complete trajectories based on the selected goals.

Autonomous Driving motion prediction +1

Intrinsically Motivated Self-supervised Learning in Reinforcement Learning

no code implementations26 Jun 2021 Yue Zhao, Chenzhuang Du, Hang Zhao, Tiejun Li

In vision-based reinforcement learning (RL) tasks, it is prevalent to assign the auxiliary task with a surrogate self-supervised loss so as to obtain more semantic representations and improve sample efficiency.

Decision Making Representation Learning +1

Co-advise: Cross Inductive Bias Distillation

no code implementations23 Jun 2021 Sucheng Ren, Zhengqi Gao, Tianyu Hua, Zihui Xue, Yonglong Tian, Shengfeng He, Hang Zhao

Transformers recently are adapted from the community of natural language processing as a promising substitute of convolution-based neural networks for visual learning tasks.

Improving Multi-Modal Learning with Uni-Modal Teachers

no code implementations21 Jun 2021 Chenzhuang Du, Tingle Li, Yichen Liu, Zixin Wen, Tianyu Hua, Yue Wang, Hang Zhao

We name this problem Modality Failure, and hypothesize that the imbalance of modalities and the implicit bias of common objectives in fusion method prevent encoders of each modality from sufficient feature learning.

Semantic Segmentation

On Feature Decorrelation in Self-Supervised Learning

no code implementations ICCV 2021 Tianyu Hua, Wenxiao Wang, Zihui Xue, Sucheng Ren, Yue Wang, Hang Zhao

In self-supervised representation learning, a common idea behind most of the state-of-the-art approaches is to enforce the robustness of the representations to predefined augmentations.

Representation Learning Self-Supervised Learning

Multimodal Knowledge Expansion

1 code implementation ICCV 2021 Zihui Xue, Sucheng Ren, Zhengqi Gao, Hang Zhao

The popularity of multimodal sensors and the accessibility of the Internet have brought us a massive amount of unlabeled multimodal data.

Denoising Knowledge Distillation

Predictive Visual Tracking: A New Benchmark and Baseline Approach

1 code implementation8 Mar 2021 Bowen Li, Yiming Li, Junjie Ye, Changhong Fu, Hang Zhao

As a crucial robotic perception capability, visual tracking has been intensively studied recently.

Visual Tracking

AETree: Areal Spatial Data Generation

no code implementations1 Jan 2021 Congcong Wen, Wenyu Han, Hang Zhao, Chen Feng

Areal spatial data represent not only geographical locations but also sizes and shapes of physical objects such as buildings in a city.

UnModNet: Learning to Unwrap a Modulo Image for High Dynamic Range Imaging

no code implementations NeurIPS 2020 Chu Zhou, Hang Zhao, Jin Han, Chang Xu, Chao Xu, Tiejun Huang, Boxin Shi

A conventional camera often suffers from over- or under-exposure when recording a real-world scene with a very high dynamic range (HDR).

Unsupervised Monocular Depth Learning in Dynamic Scenes

3 code implementations30 Oct 2020 Hanhan Li, Ariel Gordon, Hang Zhao, Vincent Casser, Anelia Angelova

We present a method for jointly training the estimation of depth, ego-motion, and a dense 3D translation field of objects relative to the scene, with monocular photometric consistency being the sole source of supervision.

Depth Estimation Translation

CLOUD: Contrastive Learning of Unsupervised Dynamics

no code implementations23 Oct 2020 Jianren Wang, Yujie Lu, Hang Zhao

Developing agents that can perform complex control tasks from high dimensional observations such as pixels is challenging due to difficulties in learning dynamics efficiently.

Contrastive Learning

Multivariate Time-series Anomaly Detection via Graph Attention Network

2 code implementations4 Sep 2020 Hang Zhao, Yujing Wang, Juanyong Duan, Congrui Huang, Defu Cao, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang

Anomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications.

Anomaly Detection Graph Attention +2

Online 3D Bin Packing with Constrained Deep Reinforcement Learning

1 code implementation26 Jun 2020 Hang Zhao, Qijin She, Chenyang Zhu, Yin Yang, Kai Xu

We solve a challenging yet practically useful variant of 3D Bin Packing Problem (3D-BPP).

3D Bin Packing

VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation

3 code implementations CVPR 2020 Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Cong-Cong Li, Cordelia Schmid

Behavior prediction in dynamic, multi-agent systems is an important problem in the context of self-driving cars, due to the complex representations and interactions of road components, including moving agents (e. g. pedestrians and vehicles) and road context information (e. g. lanes, traffic lights).

Self-Driving Cars

AlignNet: A Unifying Approach to Audio-Visual Alignment

1 code implementation12 Feb 2020 Jianren Wang, Zhaoyuan Fang, Hang Zhao

We present AlignNet, a model that synchronizes videos with reference audios under non-uniform and irregular misalignments.

Neural network with data augmentation in multi-objective prediction of multi-stage pump

no code implementations4 Feb 2020 Hang Zhao

Finally, a neural network model based on data augmentation (NNDA) is proposed for the reason that simulation cost is too high and data is scarce in mechanical simulation field especially in CFD problems.

Data Augmentation

Self-supervised Moving Vehicle Tracking with Stereo Sound

no code implementations ICCV 2019 Chuang Gan, Hang Zhao, Peihao Chen, David Cox, Antonio Torralba

At test time, the stereo-sound student network can work independently to perform object localization us-ing just stereo audio and camera meta-data, without any visual input.

Object Localization Visual Localization

Active Scene Understanding via Online Semantic Reconstruction

no code implementations18 Jun 2019 Lintao Zheng, Chenyang Zhu, Jiazhao Zhang, Hang Zhao, Hui Huang, Matthias Niessner, Kai Xu

In our method, the exploratory robot scanning is both driven by and targeting at the recognition and segmentation of semantic objects from the scene.

Scene Understanding Semantic Segmentation

Self-Supervised Audio-Visual Co-Segmentation

no code implementations18 Apr 2019 Andrew Rouditchenko, Hang Zhao, Chuang Gan, Josh Mcdermott, Antonio Torralba

Segmenting objects in images and separating sound sources in audio are challenging tasks, in part because traditional approaches require large amounts of labeled data.

Semantic Segmentation

Through-Wall Human Pose Estimation Using Radio Signals

no code implementations CVPR 2018 Ming-Min Zhao, Tianhong Li, Mohammad Abu Alsheikh, Yonglong Tian, Hang Zhao, Antonio Torralba, Dina Katabi

Yet, unlike vision-based pose estimation, the radio-based system can estimate 2D poses through walls despite never trained on such scenarios.

RF-based Pose Estimation

The Sound of Pixels

2 code implementations ECCV 2018 Hang Zhao, Chuang Gan, Andrew Rouditchenko, Carl Vondrick, Josh Mcdermott, Antonio Torralba

We introduce PixelPlayer, a system that, by leveraging large amounts of unlabeled videos, learns to locate image regions which produce sounds and separate the input sounds into a set of components that represents the sound from each pixel.

Scene Parsing Through ADE20K Dataset

no code implementations CVPR 2017 Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, Antonio Torralba

A novel network design called Cascade Segmentation Module is proposed to parse a scene into stuff, objects, and object parts in a cascade and improve over the baselines.

Scene Parsing

Open Vocabulary Scene Parsing

no code implementations ICCV 2017 Hang Zhao, Xavier Puig, Bolei Zhou, Sanja Fidler, Antonio Torralba

Recognizing arbitrary objects in the wild has been a challenging problem due to the limitations of existing classification models and datasets.

General Classification Scene Parsing

Semantic Understanding of Scenes through the ADE20K Dataset

20 code implementations18 Aug 2016 Bolei Zhou, Hang Zhao, Xavier Puig, Tete Xiao, Sanja Fidler, Adela Barriuso, Antonio Torralba

Scene parsing, or recognizing and segmenting objects and stuff in an image, is one of the key problems in computer vision.

Scene Parsing Semantic Segmentation

Loss Functions for Neural Networks for Image Processing

1 code implementation28 Nov 2015 Hang Zhao, Orazio Gallo, Iuri Frosio, Jan Kautz

Neural networks are becoming central in several areas of computer vision and image processing and different architectures have been proposed to solve specific problems.

Image Restoration

Cannot find the paper you are looking for? You can Submit a new open access paper.