activity
20222026
most citedAccelerating Reinforcement Learning for Autonomous Driving using Task-Agnostic and Ego-Centric Motion Skills

1 citations · 2 across the 10 of their papers we have counts for

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cs.CV2026

Video Generation Models are General-Purpose Vision Learners

Letian Wang, Chuhan Zhang, Rishabh Kabra +9

Driven by next-token prediction, NLP shifted from task-specific models into powerful generalist foundation models. What, then, is the equivalent catalyst needed to achieve a genera…

cs.CV2026

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving

Hao Shao, Letian Wang, Yang Zhou +5

Recent years have seen remarkable progress in autonomous driving, yet generalization to long-tail and open-world scenarios remains a major bottleneck for large-scale deployment. To…

cs.CV2026

DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning

Yang Zhou, Xiaofeng Wang, Hao Shao +8

Recently, world-action models (WAM) have emerged to bridge vision-language-action (VLA) models and world models, unifying their reasoning and instruction-following capabilities and…

cs.CV2026

SCATR: Mitigating New Instance Suppression in LiDAR-based Tracking-by-Attention via Second Chance Assignment and Track Query Dropout

Brian Cheong, Letian Wang, Sandro Papais +1

LiDAR-based tracking-by-attention (TBA) frameworks inherently suffer from high false negative errors, leading to a significant performance gap compared to traditional LiDAR-based t…

cs.CV2026

DrivingGen: A Comprehensive Benchmark for Generative Video World Models in Autonomous Driving

Yang Zhou, Hao Shao, Letian Wang +3

Video generation models, as one form of world models, have emerged as one of the most exciting frontiers in AI, promising agents the ability to imagine the future by modeling the t…

cs.CV2025

ForeSight: Multi-View Streaming Joint Object Detection and Trajectory Forecasting

Sandro Papais, Letian Wang, Brian Cheong +1

We introduce ForeSight, a novel joint detection and forecasting framework for vision-based 3D perception in autonomous vehicles. Traditional approaches treat detection and forecast…