94 citations · 404 across the 53 of their papers we have counts for
53 papers
An Empirical Analysis of Compatibility Issues for Industrial Mobile Games
Zihe Song, Yingfeng Chen, Lei Ma +4
Detecting and fixing compatibility issues is critical for mobile game development. The rapid evolution of mobile operating systems and device fragmentation make it challenging for…
Rethinking Noisy Label Learning in Real-world Annotation Scenarios from the Noise-type Perspective
Renyu Zhu, Haoyu Liu, Runze Wu +4
In this paper, we investigate the problem of learning with noisy labels in real-world annotation scenarios, where noise can be categorized into two types: factual noise and ambigui…
FlowFace++: Explicit Semantic Flow-supervised End-to-End Face Swapping
Yu Zhang, Hao Zeng, Bowen Ma +5
This work proposes a novel face-swapping framework FlowFace++, utilizing explicit semantic flow supervision and end-to-end architecture to facilitate shape-aware face-swapping. Spe…
Prioritized Trajectory Replay: A Replay Memory for Data-driven Reinforcement Learning
Jinyi Liu, Yi Ma, Jianye Hao +4
In recent years, data-driven reinforcement learning (RL), also known as offline RL, have gained significant attention. However, the role of data sampling techniques in offline RL h…
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…
Diverse 3D Hand Gesture Prediction from Body Dynamics by Bilateral Hand Disentanglement
Xingqun Qi, Chen Liu, Muyi Sun +3
Predicting natural and diverse 3D hand gestures from the upper body dynamics is a practical yet challenging task in virtual avatar creation. Previous works usually overlook the asy…
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…
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…
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…
Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning
Shanqi Liu, Yujing Hu, Runze Wu +5
Real-world cooperation often requires intensive coordination among agents simultaneously. This task has been extensively studied within the framework of cooperative multi-agent rei…
Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learning
Rundong Wang, Longtao Zheng, Wei Qiu +7
Recent advances in multi-agent reinforcement learning (MARL) allow agents to coordinate their behaviors in complex environments. However, common MARL algorithms still suffer from s…
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…
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…
FlowFace: Semantic Flow-guided Shape-aware Face Swapping
Hao Zeng, Wei Zhang, Changjie Fan +7
In this work, we propose a semantic flow-guided two-stage framework for shape-aware face swapping, namely FlowFace. Unlike most previous methods that focus on transferring the sour…
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…
EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
Yifu Yuan, Jianye Hao, Fei Ni +6
Unsupervised reinforcement learning (URL) poses a promising paradigm to learn useful behaviors in a task-agnostic environment without the guidance of extrinsic rewards to facilitat…
Distributed Multi-Robot Obstacle Avoidance via Logarithmic Map-based Deep Reinforcement Learning
Jiafeng Ma, Guangda chen, Yingfeng Chen +3
Developing a safe, stable, and efficient obstacle avoidance policy in crowded and narrow scenarios for multiple robots is challenging. Most existing studies either use centralized…
Off-Beat Multi-Agent Reinforcement Learning
Wei Qiu, Weixun Wang, Rundong Wang +7
We investigate model-free multi-agent reinforcement learning (MARL) in environments where off-beat actions are prevalent, i.e., all actions have pre-set execution durations. During…
DecBERT: Enhancing the Language Understanding of BERT with Causal Attention Masks
Ziyang Luo, Yadong Xi, Jing Ma +4
Since 2017, the Transformer-based models play critical roles in various downstream Natural Language Processing tasks. However, a common limitation of the attention mechanism utiliz…
Youling: an AI-Assisted Lyrics Creation System
Rongsheng Zhang, Xiaoxi Mao, Le Li +6
Recently, a variety of neural models have been proposed for lyrics generation. However, most previous work completes the generation process in a single pass with little human inter…
Episodic Multi-agent Reinforcement Learning with Curiosity-Driven Exploration
Lulu Zheng, Jiarui Chen, Jianhao Wang +6
Efficient exploration in deep cooperative multi-agent reinforcement learning (MARL) still remains challenging in complex coordination problems. In this paper, we introduce a novel…
RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System
Kai Wang, Zhene Zou, Minghao Zhao +7
Reinforcement learning based recommender systems (RL-based RS) aim at learning a good policy from a batch of collected data, by casting recommendations to multi-step decision-makin…
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…
LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation
Jian Guan, Zhuoer Feng, Yamei Chen +4
Standard multi-task benchmarks are essential for developing pretraining models that can generalize to various downstream tasks. Existing benchmarks for natural language processing…