35 citations · 49 across the 5 of their papers we have counts for
6 papers
DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstration
Pengyuan Wang, Fabian Manhardt, Luca Minciullo +4
The ability to successfully grasp objects is crucial in robotics, as it enables several interactive downstream applications. To this end, most approaches either compute the full 6D…
Selective Spatio-Temporal Aggregation Based Pose Refinement System: Towards Understanding Human Activities in Real-World Videos
Di Yang, Rui Dai, Yaohui Wang +4
Taking advantage of human pose data for understanding human activities has attracted much attention these days. However, state-of-the-art pose estimators struggle in obtaining high…
Toyota Smarthome Untrimmed: Real-World Untrimmed Videos for Activity Detection
Rui Dai, Srijan Das, Saurav Sharma +4
Designing activity detection systems that can be successfully deployed in daily-living environments requires datasets that pose the challenges typical of real-world scenarios. In t…
On Evaluating Weakly Supervised Action Segmentation Methods
Yaser Souri, Alexander Richard, Luca Minciullo +1
Action segmentation is the task of temporally segmenting every frame of an untrimmed video. Weakly supervised approaches to action segmentation, especially from transcripts have be…
CPS++: Improving Class-level 6D Pose and Shape Estimation From Monocular Images With Self-Supervised Learning
Fabian Manhardt, Gu Wang, Benjamin Busam +5
Contemporary monocular 6D pose estimation methods can only cope with a handful of object instances. This naturally hampers possible applications as, for instance, robots seamlessly…
Fast Weakly Supervised Action Segmentation Using Mutual Consistency
Yaser Souri, Mohsen Fayyaz, Luca Minciullo +2
Action segmentation is the task of predicting the actions for each frame of a video. As obtaining the full annotation of videos for action segmentation is expensive, weakly supervi…