113 citations · 482 across the 18 of their papers we have counts for
19 papers
SAIL: Perceptual Quality-Aware Rate Control for Cloud Gaming
Houde Qian, Chenglei Wu, Jiaxing Zhang +8
Cloud gaming streams cloud-rendered frames under strict motion-to-photon latency, yet its at-scale viability is increasingly constrained by bandwidth cost: in our study of the T cl…
ElegantVLA: Learning When to Think for Efficient Vision-Language-Action Models
Ye Li, Huanan Liu, Kangye Ji +7
Vision-Language-Action (VLA) models are a powerful paradigm for generalist robotic control. However, their high computational cost and limited control frequency hinder real-time ro…
RoboStream: Weaving Spatio-Temporal Reasoning with Memory in Vision-Language Models for Robotics
Yuzhi Huang, Jie Wu, Weijue Bu +9
Enabling reliable long-horizon robotic manipulation is a crucial step toward open-world embodied intelligence. However, VLM-based planners treat each step as an isolated observatio…
Neural Strands: Learning Hair Geometry and Appearance from Multi-View Images
Radu Alexandru Rosu, Shunsuke Saito, Ziyan Wang +3
We present Neural Strands, a novel learning framework for modeling accurate hair geometry and appearance from multi-view image inputs. The learned hair model can be rendered in rea…
Drivable Volumetric Avatars using Texel-Aligned Features
Edoardo Remelli, Timur Bagautdinov, Shunsuke Saito +8
Photorealistic telepresence requires both high-fidelity body modeling and faithful driving to enable dynamically synthesized appearance that is indistinguishable from reality. In t…
Multiface: A Dataset for Neural Face Rendering
Cheng-hsin Wuu, Ningyuan Zheng, Scott Ardisson +28
Photorealistic avatars of human faces have come a long way in recent years, yet research along this area is limited by a lack of publicly available, high-quality datasets covering…
Garment Avatars: Realistic Cloth Driving using Pattern Registration
Oshri Halimi, Fabian Prada, Tuur Stuyck +7
Virtual telepresence is the future of online communication. Clothing is an essential part of a person's identity and self-expression. Yet, ground truth data of registered clothes i…
Dressing Avatars: Deep Photorealistic Appearance for Physically Simulated Clothing
Donglai Xiang, Timur Bagautdinov, Tuur Stuyck +10
Despite recent progress in developing animatable full-body avatars, realistic modeling of clothing - one of the core aspects of human self-expression - remains an open challenge. S…
Driving-Signal Aware Full-Body Avatars
Timur Bagautdinov, Chenglei Wu, Tomas Simon +6
We present a learning-based method for building driving-signal aware full-body avatars. Our model is a conditional variational autoencoder that can be animated with incomplete driv…
Modeling Clothing as a Separate Layer for an Animatable Human Avatar
Donglai Xiang, Fabian Prada, Timur Bagautdinov +5
We have recently seen great progress in building photorealistic animatable full-body codec avatars, but generating high-fidelity animation of clothing is still difficult. To addres…
MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video
Donglai Xiang, Fabian Prada, Chenglei Wu +1
We present a method to capture temporally coherent dynamic clothing deformation from a monocular RGB video input. In contrast to the existing literature, our method does not requir…
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels
Yi Zhou, Chenglei Wu, Zimo Li +5
Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher pre…
Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning
Xin Yao, Tianchi Huang, Chenglei Wu +2
Human beings are able to master a variety of knowledge and skills with ongoing learning. By contrast, dramatic performance degradation is observed when new tasks are added to an ex…
Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs
Xin Yao, Tianchi Huang, Chenglei Wu +2
Federated learning (FL) enables on-device training over distributed networks consisting of a massive amount of modern smart devices, such as smartphones and IoT (Internet of Things…
Comyco: Quality-Aware Adaptive Video Streaming via Imitation Learning
Tianchi Huang, Chao Zhou, Rui-Xiao Zhang +3
Learning-based Adaptive Bit Rate~(ABR) method, aiming to learn outstanding strategies without any presumptions, has become one of the research hotspots for adaptive streaming. Howe…
Reactive Video Caching via long-short-term fusion approach
Rui-Xiao Zhang, Tianchi Huang, Chenglei Wu +1
Video caching has been a basic network functionality in today's network architectures. Although the abundance of caching replacement algorithms has been proposed recently, these me…
Tiyuntsong: A Self-Play Reinforcement Learning Approach for ABR Video Streaming
Tianchi Huang, Xin Yao, Chenglei Wu +3
Existing reinforcement learning~(RL)-based adaptive bitrate~(ABR) approaches outperform the previous fixed control rules based methods by improving the Quality of Experience~(QoE)…
Drone Streaming with Wi-Fi Grid Aggregation for Virtual Tour
Chenglei Wu, Zhi Wang, Shiqiang Yang
To provide a live, active and high-quality virtual touring streaming experience, we propose an unmanned drone stereoscopic streaming paradigm using a control and streaming infrastr…
Improving Crowdsourced Live Streaming with Aggregated Edge Networks
Chenglei Wu, Zhi Wang, Jiangchuan Liu +1
Recent years have witnessed a dramatic increase of user-generated video services. In such user-generated video services, crowdsourced live streaming (e.g., Periscope, Twitch) has s…