4 citations · 4 across the 6 of their papers we have counts for
7 papers
AffordanceGrasp-R1:Leveraging Reasoning-Based Affordance Segmentation with Reinforcement Learning for Robotic Grasping
Dingyi Zhou, Mu He, Zhuowei Fang +4
We introduce AffordanceGrasp-R1, a reasoning-driven affordance segmentation framework for robotic grasping that combines a chain-of-thought (CoT) cold-start strategy with reinforce…
Language-Guided Grasp Detection with Coarse-to-Fine Learning for Robotic Manipulation
Zebin Jiang, Tianle Jin, Xiangtong Yao +2
Grasping is one of the most fundamental challenging capabilities in robotic manipulation, especially in unstructured, cluttered, and semantically diverse environments. Recent resea…
TUMTraf EMOT: Event-Based Multi-Object Tracking Dataset and Baseline for Traffic Scenarios
Mengyu Li, Xingcheng Zhou, Guang Chen +2
In Intelligent Transportation Systems (ITS), multi-object tracking is primarily based on frame-based cameras. However, these cameras tend to perform poorly under dim lighting and h…
URNet: Uncertainty-aware Refinement Network for Event-based Stereo Depth Estimation
Yifeng Cheng, Alois Knoll, Hu Cao
Event cameras provide high temporal resolution, high dynamic range, and low latency, offering significant advantages over conventional frame-based cameras. In this work, we introdu…
BiSeg-SAM: Weakly-Supervised Post-Processing Framework for Boosting Binary Segmentation in Segment Anything Models
Encheng Su, Hu Cao, Alois Knoll
Accurate segmentation of polyps and skin lesions is essential for diagnosing colorectal and skin cancers. While various segmentation methods for polyps and skin lesions using fully…
CoDa-4DGS: Dynamic Gaussian Splatting with Context and Deformation Awareness for Autonomous Driving
Rui Song, Chenwei Liang, Yan Xia +5
Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms.…