activity
20232026
most citedBench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving

3 citations · 6 across the 21 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation

Songbur Wong, Xiaosong Jia, Junqi You +12

Evaluating end-to-end autonomous driving (E2E-AD) remains challenging, as existing driving simulation methods often trade off closed-loop interactivity (e.g., CARLA) and real-world…

cs.CV2026

Resolving Representation Ambiguity in Feedforward Novel View Synthesis Transformer via Semantic-Spatial Decoupling

Yihang Wu, Yihang Sun, Shaofeng Zhang +4

Transformer-based models have advanced feedforward novel view synthesis (NVS). Current architectures such as GS-LRM and LVSM mix semantic information (e.g., RGB) and spatial inform…

cs.CV2026

Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model

Tao Lin, Yuxin Du, Jiting Liu +14

Vision-Language-Action models have emerged as a promising paradigm for robotic manipulation by unifying perception, language grounding, and action generation. However, they often s…

cs.CV2026

Efficient-LVSM: Faster, Cheaper, and Better Large View Synthesis Model via Decoupled Co-Refinement Attention

Xiaosong Jia, Yihang Sun, Junqi You +5

Feedforward models for novel view synthesis (NVS) have recently advanced by transformer-based methods like LVSM, using attention among all input and target views. In this work, we…

cs.CV2025

Spatial Retrieval Augmented Autonomous Driving

Xiaosong Jia, Chenhe Zhang, Yule Jiang +8

Existing autonomous driving systems rely on onboard sensors (cameras, LiDAR, IMU, etc) for environmental perception. However, this paradigm is limited by the drive-time perception…

cs.CV2025

DriveVGGT: Calibration-Constrained Visual Geometry Transformers for Multi-Camera Autonomous Driving

Xiaosong Jia, Yanhao Liu, Yu Hong +5

Feed-forward reconstruction has been progressed rapidly, with the Visual Geometry Grounded Transformer (VGGT) being a notable baseline. However, directly applying VGGT to autonomou…