Search Results for author: Kan Chen

Found 29 papers, 14 papers with code

WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting

no code implementations7 Apr 2023 Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Mustafa, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov

To study the effect of these modular approaches, design new paradigms that mitigate these limitations, and accelerate the development of end-to-end motion forecasting models, we augment the Waymo Open Motion Dataset (WOMD) with large-scale, high-quality, diverse LiDAR data for the motion forecasting task.

Motion Forecasting

Measuring Tail Risks

no code implementations15 Sep 2022 Kan Chen, Tuoyuan Cheng

In this paper, we propose a tail risk measure based on the most probable maximum size of risk events (MPMR) that can occur over a length of time.


Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation

no code implementations7 Mar 2022 Kan Chen, Qishuo Yin, Qi Long

Motivated by the theoretical analysis, we propose a novel objective function for estimating the ATE that uses the energy distance balancing score and hence does not require correct specification of the propensity score model.

Additive models Causal Inference

Cross-Domain Adaptive Teacher for Object Detection

2 code implementations CVPR 2022 Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma, Yen-Cheng Liu, Kan Chen, Bichen Wu, Zijian He, Kris Kitani, Peter Vajda

To mitigate this problem, we propose a teacher-student framework named Adaptive Teacher (AT) which leverages domain adversarial learning and weak-strong data augmentation to address the domain gap.

Data Augmentation Domain Adaptation +2

Edge of chaos as a guiding principle for modern neural network training

no code implementations20 Jul 2021 Lin Zhang, Ling Feng, Kan Chen, Choy Heng Lai

Motivated by the edge of chaos principle behind the optimal performance of neural networks, we study the role of various hyperparameters in modern neural network training algorithms in terms of the order-chaos phase diagram.

Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability

no code implementations18 Jul 2021 Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long

Interestingly, we show a new equivalence between DP-SGD and DP-SGLD, implying that some non-Bayesian DP training naturally allows for uncertainty quantification.

Video Question Answering with Phrases via Semantic Roles

no code implementations NAACL 2021 Arka Sadhu, Kan Chen, Ram Nevatia

Video Question Answering (VidQA) evaluation metrics have been limited to a single-word answer or selecting a phrase from a fixed set of phrases.

Question Answering Video Question Answering

Unbiased Teacher for Semi-Supervised Object Detection

4 code implementations ICLR 2021 Yen-Cheng Liu, Chih-Yao Ma, Zijian He, Chia-Wen Kuo, Kan Chen, Peizhao Zhang, Bichen Wu, Zsolt Kira, Peter Vajda

To address this, we introduce Unbiased Teacher, a simple yet effective approach that jointly trains a student and a gradually progressing teacher in a mutually-beneficial manner.

Image Classification object-detection +3

Spectrum of the doubly charmed molecular pentaquarks in chiral effective field theory

no code implementations11 Feb 2021 Kan Chen, Bo wang, Shi-Lin Zhu

We perform a systematic study on the interactions of the $\Sigma_c^{(*)}D^{(*)}$ systems within the framework of chiral effective field theory.

High Energy Physics - Phenomenology High Energy Physics - Experiment High Energy Physics - Lattice Nuclear Theory

A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks

1 code implementation25 Oct 2020 Zhiqi Bu, Shiyun Xu, Kan Chen

When equipped with efficient optimization algorithms, the over-parameterized neural networks have demonstrated high level of performance even though the loss function is non-convex and non-smooth.

CPARR: Category-based Proposal Analysis for Referring Relationships

no code implementations17 Apr 2020 Chuanzi He, Haidong Zhu, Jiyang Gao, Kan Chen, Ram Nevatia

The task of referring relationships is to localize subject and object entities in an image satisfying a relationship query, which is given in the form of \texttt{<subject, predicate, object>}.

Relationship Detection Visual Relationship Detection

Video Object Grounding using Semantic Roles in Language Description

1 code implementation CVPR 2020 Arka Sadhu, Kan Chen, Ram Nevatia

We explore the task of Video Object Grounding (VOG), which grounds objects in videos referred to in natural language descriptions.

MAC: Mining Activity Concepts for Language-based Temporal Localization

3 code implementations21 Nov 2018 Runzhou Ge, Jiyang Gao, Kan Chen, Ram Nevatia

Previous methods address the problem by considering features from video sliding windows and language queries and learning a subspace to encode their correlation, which ignore rich semantic cues about activities in videos and queries.

Language-Based Temporal Localization

CTAP: Complementary Temporal Action Proposal Generation

1 code implementation ECCV 2018 Jiyang Gao, Kan Chen, Ram Nevatia

Temporal action proposal generation is an important task, akin to object proposals, temporal action proposals are intended to capture "clips" or temporal intervals in videos that are likely to contain an action.

Temporal Action Proposal Generation

Motion-Appearance Co-Memory Networks for Video Question Answering

no code implementations CVPR 2018 Jiyang Gao, Runzhou Ge, Kan Chen, Ram Nevatia

Specifically, there are three salient aspects: (1) a co-memory attention mechanism that utilizes cues from both motion and appearance to generate attention; (2) a temporal conv-deconv network to generate multi-level contextual facts; (3) a dynamic fact ensemble method to construct temporal representation dynamically for different questions.

Question Answering Video Question Answering +1

Knowledge Aided Consistency for Weakly Supervised Phrase Grounding

no code implementations CVPR 2018 Kan Chen, Jiyang Gao, Ram Nevatia

In this paper, we explore the consistency contained in both visual and language modalities, and leverage complementary external knowledge to facilitate weakly supervised grounding.

Phrase Grounding

Query-guided Regression Network with Context Policy for Phrase Grounding

no code implementations ICCV 2017 Kan Chen, Rama Kovvuri, Ram Nevatia

Given a textual description of an image, phrase grounding localizes objects in the image referred by query phrases in the description.

Phrase Grounding regression

AMC: Attention guided Multi-modal Correlation Learning for Image Search

2 code implementations CVPR 2017 Kan Chen, Trung Bui, Fang Chen, Zhaowen Wang, Ram Nevatia

According to the intent of query, attention mechanism can be introduced to adaptively balance the importance of different modalities.

Image Retrieval

TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals

1 code implementation ICCV 2017 Jiyang Gao, Zhenheng Yang, Chen Sun, Kan Chen, Ram Nevatia

Temporal Action Proposal (TAP) generation is an important problem, as fast and accurate extraction of semantically important (e. g. human actions) segments from untrimmed videos is an important step for large-scale video analysis.

regression Temporal Action Localization

Knowledge Graph Representation with Jointly Structural and Textual Encoding

no code implementations26 Nov 2016 Jiacheng Xu, Kan Chen, Xipeng Qiu, Xuanjing Huang

In this paper, we propose a novel deep architecture to utilize both structural and textual information of entities.

General Classification Knowledge Graph Embedding +2

Learning Word Embeddings from Intrinsic and Extrinsic Views

no code implementations20 Aug 2016 Jifan Chen, Kan Chen, Xipeng Qiu, Qi Zhang, Xuanjing Huang, Zheng Zhang

To prove the effectiveness of our model, we evaluate it on four tasks, including word similarity, reverse dictionaries, Wiki link prediction, and document classification.

Descriptive Document Classification +4

ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering

no code implementations18 Nov 2015 Kan Chen, Jiang Wang, Liang-Chieh Chen, Haoyuan Gao, Wei Xu, Ram Nevatia

ABC-CNN determines an attention map for an image-question pair by convolving the image feature map with configurable convolutional kernels derived from the question's semantics.

Question Answering Visual Question Answering

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