activity
20222026
most citedLifelong 3D Mapping Framework for Hand-held & Robot-mounted LiDAR Mapping Systems

15 citations · 24 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV2026

VideoWeaver: Multimodal Multi-View Video-to-Video Transfer for Embodied Agents

George Eskandar, Fengyi Shen, Mohammad Altillawi +4

Recent progress in video-to-video (V2V) translation has enabled realistic resimulation of embodied AI demonstrations, a capability that allows pretrained robot policies to be trans…

cs.RO2026

ReMem-VLA: Empowering Vision-Language-Action Model with Memory via Dual-Level Recurrent Queries

Hang Li, Fengyi Shen, Dong Chen +6

Vision-language-action (VLA) models for closed-loop robot control are typically cast under the Markov assumption, making them prone to errors on tasks requiring historical context.…

cs.CV2026

ConfCtrl: Enabling Precise Camera Control in Video Diffusion via Confidence-Aware Interpolation

Liudi Yang, George Eskandar, Fengyi Shen +5

We address the challenge of novel view synthesis from only two input images under large viewpoint changes. Existing regression-based methods lack the capacity to reconstruct unseen…

cs.CV2025

CoVAR: Co-generation of Video and Action for Robotic Manipulation via Multi-Modal Diffusion

Liudi Yang, Yang Bai, George Eskandar +5

We present a method to generate video-action pairs that follow text instructions, starting from an initial image observation and the robot's joint states. Our approach automaticall…

cs.CV2025

DRAW2ACT: Turning Depth-Encoded Trajectories into Robotic Demonstration Videos

Yang Bai, Liudi Yang, George Eskandar +4

Video diffusion models provide powerful real-world simulators for embodied AI but remain limited in controllability for robotic manipulation. Recent works on trajectory-conditioned…

cs.RO2025

Lightweight Learning from Actuation-Space Demonstrations via Flow Matching for Whole-Body Soft Robotic Grasping

Liudi Yang, Yang Bai, Yuhao Wang +4

Robotic grasping under uncertainty remains a fundamental challenge due to its uncertain and contact-rich nature. Traditional rigid robotic hands, with limited degrees of freedom an…

cs.CV2025

RoboEnvision: A Long-Horizon Video Generation Model for Multi-Task Robot Manipulation

Liudi Yang, Yang Bai, George Eskandar +7

We address the problem of generating long-horizon videos for robotic manipulation tasks. Text-to-video diffusion models have made significant progress in photorealism, language und…

cs.CV2025

RoboSwap: A GAN-driven Video Diffusion Framework For Unsupervised Robot Arm Swapping

Yang Bai, Liudi Yang, George Eskandar +5

Recent advancements in generative models have revolutionized video synthesis and editing. However, the scarcity of diverse, high-quality datasets continues to hinder video-conditio…

cs.CV2025

CE-NPBG: Connectivity Enhanced Neural Point-Based Graphics for Novel View Synthesis in Autonomous Driving Scenes

Mohammad Altillawi, Fengyi Shen, Liudi Yang +2

Current point-based approaches encounter limitations in scalability and rendering quality when using large 3D point cloud maps because using them directly for novel view synthesis…

cs.CV2025★ 8 cited

LiDAR Loop Closure Detection using Semantic Graphs with Graph Attention Networks

Liudi Yang, Ruben Mascaro, Ignacio Alzugaray +4

In this paper, we propose a novel loop closure detection algorithm that uses graph attention neural networks to encode semantic graphs to perform place recognition and then use sem…

cs.RO2025★ 15 cited

Lifelong 3D Mapping Framework for Hand-held & Robot-mounted LiDAR Mapping Systems

Liudi Yang, Sai Manoj Prakhya, Senhua Zhu +1

We propose a lifelong 3D mapping framework that is modular, cloud-native by design and more importantly, works for both hand-held and robot-mounted 3D LiDAR mapping systems. Our pr…

cs.CV2022★ 1 cited

3D Textured Shape Recovery with Learned Geometric Priors

Lei Li, Zhizheng Liu, Weining Ren +4

3D textured shape recovery from partial scans is crucial for many real-world applications. Existing approaches have demonstrated the efficacy of implicit function representation, b…