3 accepted papers
The YOLO series of models are pivotal for real-time object detection, yet their deployment on resource-constrained edge devices necessitates effective model compression. Post-Training Quantization (PTQ) offers a promising, low-cost solution, but existing methods, primarily designed for classificatio…
Semantic understanding of 3D objects is crucial in many applications such as object manipulation. However, it is hard to give a universal definition of point-level semantics that everyone would agree on. We observe that people have a consensus on semantic correspondences between two areas from diffe…
Detecting 3D objects keypoints is ofgreat interest to the areas of both graphics and computer vision. There have been several 2D and 3D keypoint datasets aiming to address this problem in a data-driven way. These datasets, however, either lack scalability or bring ambiguity to the definition of keyp…