652 citations · 1.8k across the 11 of their papers we have counts for
11 papers
Pedestrian Crossing Action Recognition and Trajectory Prediction with 3D Human Keypoints
Jiachen Li, Xinwei Shi, Feiyu Chen +9
Accurate understanding and prediction of human behaviors are critical prerequisites for autonomous vehicles, especially in highly dynamic and interactive scenarios such as intersec…
Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving
Jingxiao Zheng, Xinwei Shi, Alexander Gorban +9
3D human pose estimation (HPE) in autonomous vehicles (AV) differs from other use cases in many factors, including the 3D resolution and range of data, absence of dense depth maps,…
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction
Zhishuai Zhang, Jiyang Gao, Junhua Mao +3
Detecting pedestrians and predicting future trajectories for them are critical tasks for numerous applications, such as autonomous driving. Previous methods either treat the detect…
Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images
Junhua Mao, Jiajing Xu, Yushi Jing +1
In this paper, we focus on training and evaluating effective word embeddings with both text and visual information. More specifically, we introduce a large-scale dataset with 300 m…
Attention Correctness in Neural Image Captioning
Chenxi Liu, Junhua Mao, Fei Sha +1
Attention mechanisms have recently been introduced in deep learning for various tasks in natural language processing and computer vision. But despite their popularity, the "correct…
CNN-RNN: A Unified Framework for Multi-label Image Classification
Jiang Wang, Yi Yang, Junhua Mao +3
While deep convolutional neural networks (CNNs) have shown a great success in single-label image classification, it is important to note that real world images generally contain mu…
Generation and Comprehension of Unambiguous Object Descriptions
Junhua Mao, Jonathan Huang, Alexander Toshev +3
We propose a method that can generate an unambiguous description (known as a referring expression) of a specific object or region in an image, and which can also comprehend or inte…
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question Answering
Haoyuan Gao, Junhua Mao, Jie Zhou +3
In this paper, we present the mQA model, which is able to answer questions about the content of an image. The answer can be a sentence, a phrase or a single word. Our model contain…
Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images
Junhua Mao, Wei Xu, Yi Yang +3
In this paper, we address the task of learning novel visual concepts, and their interactions with other concepts, from a few images with sentence descriptions. Using linguistic con…
Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)
Junhua Mao, Wei Xu, Yi Yang +3
In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel image captions. It directly models the probability distribution of generating a w…
Explain Images with Multimodal Recurrent Neural Networks
Junhua Mao, Wei Xu, Yi Yang +2
In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel sentence descriptions to explain the content of images. It directly models the pr…