3 papers
cs.CV2026
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
Igor Pavlovic, Thiemo Wandel, Anton Obukhov +6
Monocular depth estimation is a ubiquitous yet highly ill-posed computer vision task, with downstream applications in scene reconstruction, computational photography, and robotics,…
cs.RO2026
ContextFlow: In-Context Flow Matching for Robot Manipulation
Jian Ding, Xianjie Dai, Roei Herzig +5
Although highly effective in vision and language domains, applying in-context learning to robotics remains challenging. Existing autoregressive in-context imitation methods discret…
cs.CV2023
Benchmarking the Robustness of LiDAR Semantic Segmentation Models
Xu Yan, Chaoda Zheng, Ying Xue +3
When using LiDAR semantic segmentation models for safety-critical applications such as autonomous driving, it is essential to understand and improve their robustness with respect t…