This paper presents a comprehensive survey on vision-based robotic grasping. We
conclude three key tasks during vision-based robotic grasping, which are object localization …

Unmanned aerial vehicles (UAVs) are increasingly becoming popular due to their use in
many commercial and military applications, and their affordability. The UAVs are equipped …

Recently, the power of unconditional image synthesis has significantly advanced through
the use of Generative Adversarial Networks (GANs). The task of inverting an image into its …

Grasping unseen objects in unconstrained, cluttered environments is an essential skill for
autonomous robotic manipulation. Despite recent progress in full 6-DoF grasp learning …

We introduce an approach for recovering the 6D pose of multiple known objects in a scene
captured by a set of input images with unknown camera viewpoints. First, we present a …

In this work, we present FFB6D, a full flow bidirectional fusion network designed for 6D pose
estimation from a single RGBD image. Our key insight is that appearance information in the …

We introduce DexYCB, a new dataset for capturing hand grasping of objects. We first
compare DexYCB with a related one through cross-dataset evaluation. We then present a …

In this work, we present a novel data-driven method for robust 6DoF object pose estimation
from a single RGBD image. Unlike previous methods that directly regressing pose …

This paper addresses the challenge of 6DoF pose estimation from a single RGB image
under severe occlusion or truncation. Many recent works have shown that a two-stage …

While 6D object pose estimation has recently made a huge leap forward, most methods can
still only handle a single or a handful of different objects, which limits their applications. To …