activity
20192024
most citedGLIB: Towards Automated Test Oracle for Graphically-Rich Applications

30 citations · 71 across the 18 of their papers we have counts for

collaborators

18 papers

cs.AI2024

XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques

Yu Xiong, Zhipeng Hu, Ye Huang +9

Reinforcement Learning (RL) has demonstrated substantial potential across diverse fields, yet understanding its decision-making process, especially in real-world scenarios where ra…

cs.CV2024

Towards a Simultaneous and Granular Identity-Expression Control in Personalized Face Generation

Renshuai Liu, Bowen Ma, Wei Zhang +5

In human-centric content generation, the pre-trained text-to-image models struggle to produce user-wanted portrait images, which retain the identity of individuals while exhibiting…

cs.AI2023★ 1 cited

AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model

Zibin Dong, Yifu Yuan, Jianye Hao +7

Aligning agent behaviors with diverse human preferences remains a challenging problem in reinforcement learning (RL), owing to the inherent abstractness and mutability of human pre…

cs.CL2023★ 1 cited

Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations

Yufeng Huang, Jiji Tang, Zhuo Chen +8

Large-scale vision-language pre-training has achieved significant performance in multi-modal understanding and generation tasks. However, existing methods often perform poorly on i…

cs.CV2023★ 6 cited

TalkCLIP: Talking Head Generation with Text-Guided Expressive Speaking Styles

Yifeng Ma, Suzhen Wang, Yu Ding +6

Audio-driven talking head generation has drawn growing attention. To produce talking head videos with desired facial expressions, previous methods rely on extra reference videos to…

cs.CV2023★ 4 cited

DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video

Zhimeng Zhang, Zhipeng Hu, Wenjin Deng +3

For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail to generate high-fidelity du…

cs.CV2023

Zero-Shot Text-to-Parameter Translation for Game Character Auto-Creation

Rui Zhao, Wei Li, Zhipeng Hu +4

Recent popular Role-Playing Games (RPGs) saw the great success of character auto-creation systems. The bone-driven face model controlled by continuous parameters (like the position…

cs.CV2023

NeFII: Inverse Rendering for Reflectance Decomposition with Near-Field Indirect Illumination

Haoqian Wu, Zhipeng Hu, Lincheng Li +3

Inverse rendering methods aim to estimate geometry, materials and illumination from multi-view RGB images. In order to achieve better decomposition, recent approaches attempt to mo…

cs.CL2023★ 2 cited

Tailoring Language Generation Models under Total Variation Distance

Haozhe Ji, Pei Ke, Zhipeng Hu +2

The standard paradigm of neural language generation adopts maximum likelihood estimation (MLE) as the optimizing method. From a distributional view, MLE in fact minimizes the Kullb…

cs.CV2023

StyleTalk: One-shot Talking Head Generation with Controllable Speaking Styles

Yifeng Ma, Suzhen Wang, Zhipeng Hu +5

Different people speak with diverse personalized speaking styles. Although existing one-shot talking head methods have made significant progress in lip sync, natural facial express…

cs.LG2022

TCFimt: Temporal Counterfactual Forecasting from Individual Multiple Treatment Perspective

Pengfei Xi, Guifeng Wang, Zhipeng Hu +8

Determining causal effects of temporal multi-intervention assists decision-making. Restricted by time-varying bias, selection bias, and interactions of multiple interventions, the…

cs.CV2022★ 6 cited

Facial Action Unit Detection and Intensity Estimation from Self-supervised Representation

Bowen Ma, Rudong An, Wei Zhang +6

As a fine-grained and local expression behavior measurement, facial action unit (FAU) analysis (e.g., detection and intensity estimation) has been documented for its time-consuming…

cs.CL2022★ 1 cited

Generating Coherent Narratives by Learning Dynamic and Discrete Entity States with a Contrastive Framework

Jian Guan, Zhenyu Yang, Rongsheng Zhang +2

Despite advances in generating fluent texts, existing pretraining models tend to attach incoherent event sequences to involved entities when generating narratives such as stories a…

cs.CL2022

LaMemo: Language Modeling with Look-Ahead Memory

Haozhe Ji, Rongsheng Zhang, Zhenyu Yang +2

Although Transformers with fully connected self-attentions are powerful to model long-term dependencies, they are struggling to scale to long texts with thousands of words in langu…

cs.LG2021★ 1 cited

Neural-to-Tree Policy Distillation with Policy Improvement Criterion

Zhao-Hua Li, Yang Yu, Yingfeng Chen +3

While deep reinforcement learning has achieved promising results in challenging decision-making tasks, the main bones of its success --- deep neural networks are mostly black-boxes…

cs.SE2021★ 30 cited

GLIB: Towards Automated Test Oracle for Graphically-Rich Applications

Ke Chen, Yufei Li, Yingfeng Chen +3

Graphically-rich applications such as games are ubiquitous with attractive visual effects of Graphical User Interface (GUI) that offers a bridge between software applications and e…

cs.MA2021★ 9 cited

Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games

Xiangyu Liu, Hangtian Jia, Ying Wen +5

Measuring and promoting policy diversity is critical for solving games with strong non-transitive dynamics where strategic cycles exist, and there is no consistent winner (e.g., Ro…

cs.LG2019★ 10 cited

Learning Action-Transferable Policy with Action Embedding

Yu Chen, Yingfeng Chen, Zhipeng Hu +4

Transfer learning (TL) is a promising way to improve the sample efficiency of reinforcement learning. However, how to efficiently transfer knowledge across tasks with different sta…