Search Results for author: YuFei Wang

Found 94 papers, 43 papers with code

Edit3K: Universal Representation Learning for Video Editing Components

no code implementations24 Mar 2024 Xin Gu, Libo Zhang, Fan Chen, Longyin Wen, YuFei Wang, Tiejian Luo, Sijie Zhu

Each video in our dataset is rendered by various image/video materials with a single editing component, which supports atomic visual understanding of different editing components.

Representation Learning Retrieval +1

Tri-Perspective View Decomposition for Geometry-Aware Depth Completion

no code implementations22 Mar 2024 Zhiqiang Yan, Yuankai Lin, Kun Wang, Yupeng Zheng, YuFei Wang, Zhenyu Zhang, Jun Li, Jian Yang

Depth completion is a vital task for autonomous driving, as it involves reconstructing the precise 3D geometry of a scene from sparse and noisy depth measurements.

Autonomous Driving Depth Completion

Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI

1 code implementation15 Mar 2024 Chong Wang, Lanqing Guo, YuFei Wang, Hao Cheng, Yi Yu, Bihan Wen

Starting from decomposing the original maximum-a-posteriori problem of accelerated MRI, we present a rigorous derivation of the proposed PDAC framework, which could be further unfolded into an end-to-end trainable network.

MRI Reconstruction

Learning to Edit: Aligning LLMs with Knowledge Editing

1 code implementation19 Feb 2024 Yuxin Jiang, YuFei Wang, Chuhan Wu, Wanjun Zhong, Xingshan Zeng, Jiahui Gao, Liangyou Li, Xin Jiang, Lifeng Shang, Ruiming Tang, Qun Liu, Wei Wang

Knowledge editing techniques, aiming to efficiently modify a minor proportion of knowledge in large language models (LLMs) without negatively impacting performance across other inputs, have garnered widespread attention.

knowledge editing Philosophy

Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation

1 code implementation16 Feb 2024 Lanqing Guo, Yingqing He, Haoxin Chen, Menghan Xia, Xiaodong Cun, YuFei Wang, Siyu Huang, Yong Zhang, Xintao Wang, Qifeng Chen, Ying Shan, Bihan Wen

Diffusion models have proven to be highly effective in image and video generation; however, they still face composition challenges when generating images of varying sizes due to single-scale training data.

Video Generation

DiffTOP: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation Learning

no code implementations8 Feb 2024 Weikang Wan, YuFei Wang, Zackory Erickson, David Held

The key to our approach is to leverage the recent progress in differentiable trajectory optimization, which enables computing the gradients of the loss with respect to the parameters of trajectory optimization.

Imitation Learning

RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback

no code implementations6 Feb 2024 YuFei Wang, Zhanyi Sun, Jesse Zhang, Zhou Xian, Erdem Biyik, David Held, Zackory Erickson

Reward engineering has long been a challenge in Reinforcement Learning (RL) research, as it often requires extensive human effort and iterative processes of trial-and-error to design effective reward functions.

reinforcement-learning Reinforcement Learning (RL)

MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models

1 code implementation30 Jan 2024 Wai-Chung Kwan, Xingshan Zeng, Yuxin Jiang, YuFei Wang, Liangyou Li, Lifeng Shang, Xin Jiang, Qun Liu, Kam-Fai Wong

Large language models (LLMs) are increasingly relied upon for complex multi-turn conversations across diverse real-world applications.

YODA: Teacher-Student Progressive Learning for Language Models

no code implementations28 Jan 2024 Jianqiao Lu, Wanjun Zhong, YuFei Wang, Zhijiang Guo, Qi Zhu, Wenyong Huang, Yanlin Wang, Fei Mi, Baojun Wang, Yasheng Wang, Lifeng Shang, Xin Jiang, Qun Liu

With the teacher's guidance, the student learns to iteratively refine its answer with feedback, and forms a robust and comprehensive understanding of the posed questions.

GSM8K Math

Importance-Aware Data Augmentation for Document-Level Neural Machine Translation

no code implementations27 Jan 2024 Minghao Wu, YuFei Wang, George Foster, Lizhen Qu, Gholamreza Haffari

Document-level neural machine translation (DocNMT) aims to generate translations that are both coherent and cohesive, in contrast to its sentence-level counterpart.

Data Augmentation Machine Translation +2

UniMS-RAG: A Unified Multi-source Retrieval-Augmented Generation for Personalized Dialogue Systems

no code implementations24 Jan 2024 Hongru Wang, WenYu Huang, Yang Deng, Rui Wang, Zezhong Wang, YuFei Wang, Fei Mi, Jeff Z. Pan, Kam-Fai Wong

To better plan and incorporate the use of multiple sources in generating personalized response, we firstly decompose it into three sub-tasks: Knowledge Source Selection, Knowledge Retrieval, and Response Generation.

Response Generation Retrieval

G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model

1 code implementation18 Dec 2023 Jiahui Gao, Renjie Pi, Jipeng Zhang, Jiacheng Ye, Wanjun Zhong, YuFei Wang, Lanqing Hong, Jianhua Han, Hang Xu, Zhenguo Li, Lingpeng Kong

We first analyze the limitations of current Multimodal Large Language Models (MLLMs) in this area: they struggle to accurately comprehending basic geometric elements and their relationships.

Language Modelling Large Language Model

A Survey of the Evolution of Language Model-Based Dialogue Systems

no code implementations28 Nov 2023 Hongru Wang, Lingzhi Wang, Yiming Du, Liang Chen, Jingyan Zhou, YuFei Wang, Kam-Fai Wong

This survey delves into the historical trajectory of dialogue systems, elucidating their intricate relationship with advancements in language models by categorizing this evolution into four distinct stages, each marked by pivotal LM breakthroughs: 1) Early_Stage: characterized by statistical LMs, resulting in rule-based or machine-learning-driven dialogue_systems; 2) Independent development of TOD and ODD based on neural_language_models (NLM; e. g., LSTM and GRU), since NLMs lack intrinsic knowledge in their parameters; 3) fusion between different types of dialogue systems with the advert of pre-trained_language_models (PLMs), starting from the fusion between four_sub-tasks_within_TOD, and then TOD_with_ODD; and 4) current LLM-based_dialogue_system, wherein LLMs can be used to conduct TOD and ODD seamlessly.

Language Modelling

SinSR: Diffusion-Based Image Super-Resolution in a Single Step

1 code implementation23 Nov 2023 YuFei Wang, Wenhan Yang, Xinyuan Chen, Yaohui Wang, Lanqing Guo, Lap-Pui Chau, Ziwei Liu, Yu Qiao, Alex C. Kot, Bihan Wen

Extensive experiments conducted on synthetic and real-world datasets demonstrate that the proposed method can achieve comparable or even superior performance compared to both previous SOTA methods and the teacher model, in just one sampling step, resulting in a remarkable up to x10 speedup for inference.

Image Super-Resolution

RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation

no code implementations2 Nov 2023 YuFei Wang, Zhou Xian, Feng Chen, Tsun-Hsuan Wang, Yian Wang, Zackory Erickson, David Held, Chuang Gan

We present RoboGen, a generative robotic agent that automatically learns diverse robotic skills at scale via generative simulation.

Motion Planning

FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models

1 code implementation31 Oct 2023 Yuxin Jiang, YuFei Wang, Xingshan Zeng, Wanjun Zhong, Liangyou Li, Fei Mi, Lifeng Shang, Xin Jiang, Qun Liu, Wei Wang

To fill this research gap, in this paper, we propose FollowBench, a Multi-level Fine-grained Constraints Following Benchmark for LLMs.

Instruction Following

LRRU: Long-short Range Recurrent Updating Networks for Depth Completion

no code implementations ICCV 2023 YuFei Wang, Bo Li, Ge Zhang, Qi Liu, Tao Gao, Yuchao Dai

Existing deep learning-based depth completion methods generally employ massive stacked layers to predict the dense depth map from sparse input data.

Depth Completion

SELF: Self-Evolution with Language Feedback

no code implementations1 Oct 2023 Jianqiao Lu, Wanjun Zhong, Wenyong Huang, YuFei Wang, Qi Zhu, Fei Mi, Baojun Wang, Weichao Wang, Xingshan Zeng, Lifeng Shang, Xin Jiang, Qun Liu

SELF initiates with a meta-skill learning process that equips the LLMs with capabilities for self-feedback and self-refinement.

Language Modelling Large Language Model

Towards Lexical Analysis of Dog Vocalizations via Online Videos

no code implementations21 Sep 2023 YuFei Wang, Chunhao Zhang, Jieyi Huang, Mengyue Wu, Kenny Zhu

This study presents a data-driven investigation into the semantics of dog vocalizations via correlating different sound types with consistent semantics.

Lexical Analysis

Does My Dog ''Speak'' Like Me? The Acoustic Correlation between Pet Dogs and Their Human Owners

no code implementations21 Sep 2023 Jieyi Huang, Chunhao Zhang, YuFei Wang, Mengyue Wu, Kenny Zhu

How hosts language influence their pets' vocalization is an interesting yet underexplored problem.

Decomposed Guided Dynamic Filters for Efficient RGB-Guided Depth Completion

no code implementations5 Sep 2023 YuFei Wang, Yuxin Mao, Qi Liu, Yuchao Dai

The decomposed filters not only maintain the favorable properties of guided dynamic filters as being content-dependent and spatially-variant, but also reduce model parameters and hardware costs, as the learned adaptors are decoupled with the number of feature channels.

Depth Completion object-detection +2

Investigating the Learning Behaviour of In-context Learning: A Comparison with Supervised Learning

1 code implementation28 Jul 2023 Xindi Wang, YuFei Wang, Can Xu, Xiubo Geng, BoWen Zhang, Chongyang Tao, Frank Rudzicz, Robert E. Mercer, Daxin Jiang

Large language models (LLMs) have shown remarkable capacity for in-context learning (ICL), where learning a new task from just a few training examples is done without being explicitly pre-trained.

In-Context Learning

Aligning Large Language Models with Human: A Survey

1 code implementation24 Jul 2023 YuFei Wang, Wanjun Zhong, Liangyou Li, Fei Mi, Xingshan Zeng, Wenyong Huang, Lifeng Shang, Xin Jiang, Qun Liu

(2) Training methodologies: a detailed review of the prevailing training methods employed for LLM alignment.

ExposureDiffusion: Learning to Expose for Low-light Image Enhancement

1 code implementation ICCV 2023 YuFei Wang, Yi Yu, Wenhan Yang, Lanqing Guo, Lap-Pui Chau, Alex C. Kot, Bihan Wen

Different from a vanilla diffusion model that has to perform Gaussian denoising, with the injected physics-based exposure model, our restoration process can directly start from a noisy image instead of pure noise.

Image Denoising Low-Light Image Enhancement

Separate-and-Aggregate: A Transformer-based Patch Refinement Model for Knowledge Graph Completion

no code implementations11 Jul 2023 Chen Chen, YuFei Wang, Yang Zhang, Quan Z. Sheng, Kwok-Yan Lam

Previous KGC methods typically represent knowledge graph entities and relations as trainable continuous embeddings and fuse the embeddings of the entity $h$ (or $t$) and relation $r$ into hidden representations of query $(h, r, ?

Inductive Bias Relation

Enhancing Low-Light Images Using Infrared-Encoded Images

no code implementations9 Jul 2023 Shulin Tian, YuFei Wang, Renjie Wan, Wenhan Yang, Alex C. Kot, Bihan Wen

In this work, we propose a novel approach to increase the visibility of images captured under low-light environments by removing the in-camera infrared (IR) cut-off filter, which allows for the capture of more photons and results in improved signal-to-noise ratio due to the inclusion of information from the IR spectrum.

Low-Light Image Enhancement

Beyond Learned Metadata-based Raw Image Reconstruction

1 code implementation21 Jun 2023 YuFei Wang, Yi Yu, Wenhan Yang, Lanqing Guo, Lap-Pui Chau, Alex C. Kot, Bihan Wen

Besides, we propose a novel design of the context model, which can better predict the order masks of encoding/decoding based on both the sRGB image and the masks of already processed features.

Image Compression Image Reconstruction +1

Source Code Data Augmentation for Deep Learning: A Survey

1 code implementation31 May 2023 Terry Yue Zhuo, Zhou Yang, Zhensu Sun, YuFei Wang, Li Li, Xiaoning Du, Zhenchang Xing, David Lo

This paper fills this gap by conducting a comprehensive and integrative survey of data augmentation for source code, wherein we systematically compile and encapsulate existing literature to provide a comprehensive overview of the field.

Data Augmentation

Turning Flowchart into Dialog: Augmenting Flowchart-grounded Troubleshooting Dialogs via Synthetic Data Generation

1 code implementation2 May 2023 Haolan Zhan, Sameen Maruf, Lizhen Qu, YuFei Wang, Ingrid Zukerman, Gholamreza Haffari

Flowchart-grounded troubleshooting dialogue (FTD) systems, which follow the instructions of a flowchart to diagnose users' problems in specific domains (e. g., vehicle, laptop), have been gaining research interest in recent years.

Data Augmentation Response Generation +2

Text with Knowledge Graph Augmented Transformer for Video Captioning

no code implementations CVPR 2023 Xin Gu, Guang Chen, YuFei Wang, Libo Zhang, Tiejian Luo, Longyin Wen

Meanwhile, the internal stream is designed to exploit the multi-modality information in videos (e. g., the appearance of video frames, speech transcripts, and video captions) to ensure the quality of caption results.

Video Captioning

Temporal Coherent Test-Time Optimization for Robust Video Classification

no code implementations28 Feb 2023 Chenyu Yi, Siyuan Yang, YuFei Wang, Haoliang Li, Yap-Peng Tan, Alex C. Kot

To exploit information in video with self-supervised learning, TeCo uses global content from video clips and optimizes models for entropy minimization.

Classification Self-Supervised Learning +1

Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger

no code implementations CVPR 2023 Yi Yu, YuFei Wang, Wenhan Yang, Shijian Lu, Yap-Peng Tan, Alex C. Kot

Extensive experiments show that with our trained trigger injection models and simple modification of encoder parameters (of the compression model), the proposed attack can successfully inject several backdoors with corresponding triggers in a single image compression model.

Backdoor Attack Face Recognition +2

Raw Image Reconstruction with Learned Compact Metadata

1 code implementation CVPR 2023 YuFei Wang, Yi Yu, Wenhan Yang, Lanqing Guo, Lap-Pui Chau, Alex Kot, Bihan Wen

While raw images exhibit advantages over sRGB images (e. g., linearity and fine-grained quantization level), they are not widely used by common users due to the large storage requirements.

Image Compression Image Reconstruction +1

Removing Image Artifacts From Scratched Lens Protectors

1 code implementation11 Feb 2023 YuFei Wang, Renjie Wan, Wenhan Yang, Bihan Wen, Lap-Pui Chau, Alex C. Kot

Removing image artifacts from the scratched lens protector is inherently challenging due to the occasional flare artifacts and the co-occurring interference within mixed artifacts.

JPEG Artifact Removal

Let's Negotiate! A Survey of Negotiation Dialogue Systems

no code implementations18 Dec 2022 Haolan Zhan, YuFei Wang, Tao Feng, Yuncheng Hua, Suraj Sharma, Zhuang Li, Lizhen Qu, Gholamreza Haffari

Negotiation is one of the crucial abilities in human communication, and there has been a resurgent research interest in negotiation dialogue systems recently, which goal is to empower intelligent agents with such ability that can efficiently help humans resolve conflicts or reach beneficial agreements.

CU-Net: LiDAR Depth-Only Completion With Coupled U-Net

1 code implementation26 Oct 2022 YuFei Wang, Yuchao Dai, Qi Liu, Peng Yang, Jiadai Sun, Bo Li

We find that existing depth-only methods can obtain satisfactory results in the areas where the measurement points are almost accurate and evenly distributed (denoted as normal areas), while the performance is limited in the areas where the foreground and background points are overlapped due to occlusion (denoted as overlap areas) and the areas where there are no measurement points around (denoted as blank areas) since the methods have no reliable input information in these areas.

Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion

1 code implementation COLING 2022 Chen Chen, YuFei Wang, Bing Li, Kwok-Yan Lam

To remedy the KG structure information loss from the "flat" text, we further improve the input representations of entities and relations, and the inference algorithm in KG-S2S.

Knowledge Graph Completion

Visual Haptic Reasoning: Estimating Contact Forces by Observing Deformable Object Interactions

no code implementations11 Aug 2022 YuFei Wang, David Held, Zackory Erickson

Robotic manipulation of highly deformable cloth presents a promising opportunity to assist people with several daily tasks, such as washing dishes; folding laundry; or dressing, bathing, and hygiene assistance for individuals with severe motor impairments.

Dual-Stream Transformer for Generic Event Boundary Captioning

1 code implementation7 Jul 2022 Xin Gu, Hanhua Ye, Guang Chen, YuFei Wang, Libo Zhang, Longyin Wen

This paper describes our champion solution for the CVPR2022 Generic Event Boundary Captioning (GEBC) competition.

Boundary Captioning

Structured Context Transformer for Generic Event Boundary Detection

no code implementations7 Jun 2022 CongCong Li, Xinyao Wang, Dexiang Hong, YuFei Wang, Libo Zhang, Tiejian Luo, Longyin Wen

To capture temporal context information of each frame, we design the structure context transformer (SC-Transformer) by re-partitioning input frame sequence.

Boundary Detection Generic Event Boundary Detection

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

Attention-based Feature Decomposition-Reconstruction Network for Scene Text Detection

no code implementations29 Nov 2021 Qi Zhao, YuFei Wang, Shuchang Lyu, Lijiang Chen

In this paper, we propose attention-based feature decomposition-reconstruction network for scene text detection, which utilizes contextual information and low-level feature to enhance the performance of segmentation-based text detector.

Scene Text Detection Segmentation +1

FabricFlowNet: Bimanual Cloth Manipulation with a Flow-based Policy

1 code implementation10 Nov 2021 Thomas Weng, Sujay Bajracharya, YuFei Wang, Khush Agrawal, David Held

We introduce FabricFlowNet (FFN), a cloth manipulation policy that leverages flow as both an input and as an action representation to improve performance.

Motion Estimation Optical Flow Estimation

Disentangled Feature Representation for Few-shot Image Classification

1 code implementation26 Sep 2021 Hao Cheng, YuFei Wang, Haoliang Li, Alex C. Kot, Bihan Wen

In this work, we propose a novel Disentangled Feature Representation framework, dubbed DFR, for few-shot learning applications.

Benchmarking Classification +3

Variational Disentanglement for Domain Generalization

1 code implementation13 Sep 2021 YuFei Wang, Haoliang Li, Hao Cheng, Bihan Wen, Lap-Pui Chau, Alex C. Kot

Domain generalization aims to learn an invariant model that can generalize well to the unseen target domain.

Disentanglement Domain Generalization +1

Low-Light Image Enhancement with Normalizing Flow

1 code implementation13 Sep 2021 YuFei Wang, Renjie Wan, Wenhan Yang, Haoliang Li, Lap-Pui Chau, Alex C. Kot

To enhance low-light images to normally-exposed ones is highly ill-posed, namely that the mapping relationship between them is one-to-many.

Low-Light Image Enhancement

Mention Flags (MF): Constraining Transformer-based Text Generators

1 code implementation ACL 2021 YuFei Wang, Ian Wood, Stephen Wan, Mark Dras, Mark Johnson

In this paper, we propose Mention Flags (MF), which traces whether lexical constraints are satisfied in the generated outputs in an S2S decoder.

Common Sense Reasoning Text Generation

Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation

no code implementations NeurIPS 2021 YuFei Wang, Can Xu, Huang Hu, Chongyang Tao, Stephen Wan, Mark Dras, Mark Johnson, Daxin Jiang

Sequence-to-Sequence (S2S) neural text generation models, especially the pre-trained ones (e. g., BART and T5), have exhibited compelling performance on various natural language generation tasks.

Text Generation

Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillation

no code implementations6 Jul 2021 YuFei Wang, Haoliang Li, Lap-Pui Chau, Alex C. Kot

Though convolutional neural networks are widely used in different tasks, lack of generalization capability in the absence of sufficient and representative data is one of the challenges that hinder their practical application.

Domain Generalization Image Classification +1

Learning Visible Connectivity Dynamics for Cloth Smoothing

1 code implementation21 May 2021 Xingyu Lin, YuFei Wang, Zixuan Huang, David Held

Robotic manipulation of cloth remains challenging for robotics due to the complex dynamics of the cloth, lack of a low-dimensional state representation, and self-occlusions.

Deformable Object Manipulation Inductive Bias

Privacy-Preserving Constrained Domain Generalization via Gradient Alignment

no code implementations14 May 2021 Chris Xing Tian, Haoliang Li, YuFei Wang, Shiqi Wang

However, due to the issue of limited dataset availability and the strict legal and ethical requirements for patient privacy protection, the broad applications of medical imaging classification driven by DNN with large-scale training data have been largely hindered.

Domain Generalization Federated Learning +3

ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning

no code implementations EACL 2021 YuFei Wang, Ian D. Wood, Stephen Wan, Mark Johnson

In this paper, we focus on this challenge and propose the ECOL-R model (Encouraging Copying of Object Labels with Reinforced Learning), a copy-augmented transformer model that is encouraged to accurately describe the novel object labels.

Image Captioning Object +2

SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation

2 code implementations14 Nov 2020 Xingyu Lin, YuFei Wang, Jake Olkin, David Held

Further, we evaluate a variety of algorithms on these tasks and highlight challenges for reinforcement learning algorithms, including dealing with a state representation that has a high intrinsic dimensionality and is partially observable.

Benchmarking Deformable Object Manipulation +4

ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning

1 code implementation13 Nov 2020 YuFei Wang, Gautham Narayan Narasimhan, Xingyu Lin, Brian Okorn, David Held

Current image-based reinforcement learning (RL) algorithms typically operate on the whole image without performing object-level reasoning.

Multi-Goal Reinforcement Learning Object +2

f-IRL: Inverse Reinforcement Learning via State Marginal Matching

1 code implementation9 Nov 2020 Tianwei Ni, Harshit Sikchi, YuFei Wang, Tejus Gupta, Lisa Lee, Benjamin Eysenbach

Our method outperforms adversarial imitation learning methods in terms of sample efficiency and the required number of expert trajectories on IRL benchmarks.

Imitation Learning reinforcement-learning +1

Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems

no code implementations15 Sep 2020 Haoliang Li, Yufei Wang, Xiaofei Xie, Yang Liu, Shiqi Wang, Renjie Wan, Lap-Pui Chau, Alex C. Kot

In this paper, we propose a novel black-box backdoor attack technique on face recognition systems, which can be conducted without the knowledge of the targeted DNN model.

Backdoor Attack Face Recognition

Heterogeneous Domain Generalization via Domain Mixup

no code implementations11 Sep 2020 Yufei Wang, Haoliang Li, Alex C. Kot

One of the main drawbacks of deep Convolutional Neural Networks (DCNN) is that they lack generalization capability.

Domain Generalization

Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient

1 code implementation3 Jul 2020 Yufei Wang, Tianwei Ni

Our method is built upon the Soft Actor-Critic (SAC) algorithm, which uses an "entropy temperature" that balances the original task reward and the policy entropy, and hence controls the trade-off between exploitation and exploration.

Benchmarking

UniDual: A Unified Model for Image and Video Understanding

no code implementations10 Jun 2019 Yufei Wang, Du Tran, Lorenzo Torresani

It consists of a shared 2D spatial convolution followed by two parallel point-wise convolutional layers, one devoted to images and the other one used for videos.

Multi-Task Learning Video Understanding

How to best use Syntax in Semantic Role Labelling

1 code implementation ACL 2019 Yufei Wang, Mark Johnson, Stephen Wan, Yifang Sun, Wei Wang

There are many different ways in which external information might be used in an NLP task.

Semantic Role Labeling

Beyond Exponentially Discounted Sum: Automatic Learning of Return Function

no code implementations28 May 2019 Yufei Wang, Qiwei Ye, Tie-Yan Liu

In reinforcement learning, Return, which is the weighted accumulated future rewards, and Value, which is the expected return, serve as the objective that guides the learning of the policy.

Atari Games Meta-Learning +2

nocaps: novel object captioning at scale

2 code implementations ICCV 2019 Harsh Agrawal, Karan Desai, YuFei Wang, Xinlei Chen, Rishabh Jain, Mark Johnson, Dhruv Batra, Devi Parikh, Stefan Lee, Peter Anderson

To encourage the development of image captioning models that can learn visual concepts from alternative data sources, such as object detection datasets, we present the first large-scale benchmark for this task.

Image Captioning Object +2

How to improve the interpretability of kernel learning

no code implementations21 Nov 2018 Jinwei Zhao, Qizhou Wang, YuFei Wang, Yu Liu, Zhenghao Shi, Xinhong Hei

In this paper, a quantitative index of the interpretability is proposed and its rationality is proved, and equilibrium problem between the interpretability and the generalization performance is analyzed.

BIG-bench Machine Learning

How far from automatically interpreting deep learning

no code implementations19 Nov 2018 Jinwei Zhao, Qizhou Wang, YuFei Wang, Xinhong Hei, Yu Liu

In other words, there is a gap between the deep learning model and the cognitive mode.

Deep Reinforcement Learning for Green Security Games with Real-Time Information

no code implementations6 Nov 2018 Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang

Green Security Games (GSGs) have been proposed and applied to optimize patrols conducted by law enforcement agencies in green security domains such as combating poaching, illegal logging and overfishing.

Q-Learning reinforcement-learning +1

Concept Mask: Large-Scale Segmentation from Semantic Concepts

no code implementations ECCV 2018 Yufei Wang, Zhe Lin, Xiaohui Shen, Jianming Zhang, Scott Cohen

Then, we refine and extend the embedding network to predict an attention map, using a curated dataset with bounding box annotations on 750 concepts.

Image Segmentation Segmentation +1

Recognizing and Curating Photo Albums via Event-Specific Image Importance

1 code implementation19 Jul 2017 Yufei Wang, Zhe Lin, Xiaohui Shen, Radomir Mech, Gavin Miller, Garrison W. Cottrell

Automatic organization of personal photos is a problem with many real world ap- plications, and can be divided into two main tasks: recognizing the event type of the photo collection, and selecting interesting images from the collection.

Vocal Bursts Type Prediction

Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition

no code implementations CVPR 2017 Yufei Wang, Zhe Lin, Xiaohui Shen, Scott Cohen, Garrison W. Cottrell

Furthermore, our algorithm can generate descriptions with varied length, benefiting from the separate control of the skeleton and attributes.

Attribute Image Captioning +2

Event-Specific Image Importance

no code implementations CVPR 2016 Yufei Wang, Zhe Lin, Xiaohui Shen, Radomir Mech, Gavin Miller, Garrison W. Cottrell

In this paper, we show that the selection of important images is consistent among different viewers, and that this selection process is related to the event type of the album.

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