collaborators

10 papers

cs.CV2026

Zero-Shot Depth from Defocus

Yiming Zuo, Hongyu Wen, Venkat Subramanian +5

Depth from Defocus (DfD) is the task of estimating a dense metric depth map from a focus stack. Unlike previous works overfitting to a certain dataset, this paper focuses on the ch…

cs.CV2026

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation

Lili Gao, Yanbo Xu, William Koch +8

We introduce ScenarioControl, the first vision-language control mechanism for learned driving scenario generation. Given a text prompt or an input image, Scenario-Control synthesiz…

cs.CV2026

Telescope: Learnable Hyperbolic Foveation for Ultra-Long-Range Object Detection

Parker Ewen, Dmitriy Rivkin, Mario Bijelic +1

Autonomous highway driving, especially for long-haul heavy trucks, requires detecting objects at long ranges beyond 500 meters to satisfy braking distance requirements at high spee…

cs.CV2026

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation

Dmitriy Rivkin, Parker Ewen, Lili Gao +5

Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previous frames. However, this recurrent mec…

cs.CV2026

TruckDrive: Long-Range Autonomous Highway Driving Dataset

Filippo Ghilotti, Edoardo Palladin, Samuel Brucker +3

Safe highway autonomy for heavy trucks remains an open and unsolved challenge: due to long braking distances, scene understanding of hundreds of meters is required for anticipatory…

cs.CV2026

UniLiPs: Unified LiDAR Pseudo-Labeling with Geometry-Grounded Dynamic Scene Decomposition

Filippo Ghilotti, Samuel Brucker, Nahku Saidy +3

Unlabeled LiDAR logs, in autonomous driving applications, are inherently a gold mine of dense 3D geometry hiding in plain sight - yet they are almost useless without human labels,…