89 citations · 151 across the 12 of their papers we have counts for
12 papers
Part-Guided 3D RL for Sim2Real Articulated Object Manipulation
Pengwei Xie, Rui Chen, Siang Chen +6
Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots. Existing learning-based solutions mainly focus on visual afforda…
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability
Xuanlin Li, Yunhao Fang, Minghua Liu +3
Large vision-language models have achieved outstanding performance, but their size and computational requirements make their deployment on resource-constrained devices and time-sen…
KAFA: Rethinking Image Ad Understanding with Knowledge-Augmented Feature Adaptation of Vision-Language Models
Zhiwei Jia, Pradyumna Narayana, Arjun R. Akula +4
Image ad understanding is a crucial task with wide real-world applications. Although highly challenging with the involvement of diverse atypical scenes, real-world entities, and re…
Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction
Hansheng Chen, Jiatao Gu, Anpei Chen +4
3D-aware image synthesis encompasses a variety of tasks, such as scene generation and novel view synthesis from images. Despite numerous task-specific methods, developing a compreh…
EMVLight: a Multi-agent Reinforcement Learning Framework for an Emergency Vehicle Decentralized Routing and Traffic Signal Control System
Haoran Su, Yaofeng D. Zhong, Joseph Y. J. Chow +2
Emergency vehicles (EMVs) play a crucial role in responding to time-critical calls such as medical emergencies and fire outbreaks in urban areas. Existing methods for EMV dispatch…
FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization
Xingchao Liu, Chengyue Gong, Lemeng Wu +3
Generating images from natural language instructions is an intriguing yet highly challenging task. We approach text-to-image generation by combining the power of the retrained CLIP…
A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles
Haoran Su, Yaofeng Desmond Zhong, Biswadip Dey +1
Emergency vehicles (EMVs) play a critical role in a city's response to time-critical events such as medical emergencies and fire outbreaks. The existing approaches to reduce EMV tr…
EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles
Haoran Su, Yaofeng Desmond Zhong, Biswadip Dey +1
Emergency vehicles (EMVs) play a crucial role in responding to time-critical events such as medical emergencies and fire outbreaks in an urban area. The less time EMVs spend travel…
Particle Cloud Generation with Message Passing Generative Adversarial Networks
Raghav Kansal, Javier Duarte, Hao Su +6
In high energy physics (HEP), jets are collections of correlated particles produced ubiquitously in particle collisions such as those at the CERN Large Hadron Collider (LHC). Machi…
A Hybrid Queuing Model for Coordinated Vehicle Platooning on Mixed-Autonomy Highways: Training and Validation
Haoran Su, Zhengjie Ji, Karl. H. Johansson +1
Platooning of connected and autonomous vehicles (CAVs) is an emerging technology with a strong potential for throughput improvement and fuel reduction. Adequate macroscopic models…
V2I Connectivity-Based Dynamic Queue-Jump Lane for Emergency Vehicles: A Deep Reinforcement Learning Approach
Haoran Su, Kejian Shi, Li Jin +1
Emergency vehicle (EMV) service is a key function of cities and is exceedingly challenging due to urban traffic congestion. A main reason behind EMV service delay is the lack of co…
Dynamic Queue-Jump Lane for Emergency Vehicles under Partially Connected Settings: A Multi-Agent Deep Reinforcement Learning Approach
Haoran Su, Kejian Shi, Joseph. Y. J. Chow +1
Emergency vehicle (EMV) service is a key function of cities and is exceedingly challenging due to urban traffic congestion. The main reason behind EMV service delay is the lack of…