activity
20182024
most citedDexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Video

5 citations · 7 across the 3 of their papers we have counts for

collaborators

6 papers

cs.RO2024

ScrewMimic: Bimanual Imitation from Human Videos with Screw Space Projection

Arpit Bahety, Priyanka Mandikal, Ben Abbatematteo +1

Bimanual manipulation is a longstanding challenge in robotics due to the large number of degrees of freedom and the strict spatial and temporal synchronization required to generate…

cs.RO20225 cited

DexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Video

Priyanka Mandikal, Kristen Grauman

Dexterous multi-fingered robotic hands have a formidable action space, yet their morphological similarity to the human hand holds immense potential to accelerate robot learning. We…

cs.CV20192 cited

Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network

Priyanka Mandikal, R. Venkatesh Babu

Reconstructing a high-resolution 3D model of an object is a challenging task in computer vision. Designing scalable and light-weight architectures is crucial while addressing this…

cs.CV2018

CAPNet: Continuous Approximation Projection For 3D Point Cloud Reconstruction Using 2D Supervision

Navaneet K L, Priyanka Mandikal, Mayank Agarwal +1

Knowledge of 3D properties of objects is a necessity in order to build effective computer vision systems. However, lack of large scale 3D datasets can be a major constraint for dat…

cs.CV2018

3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction From a Single Image

Priyanka Mandikal, Navaneet K L, R. Venkatesh Babu

We propose a mechanism to reconstruct part annotated 3D point clouds of objects given just a single input image. We demonstrate that jointly training for both reconstruction and se…

cs.CV2018

3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image

Priyanka Mandikal, K L Navaneet, Mayank Agarwal +1

3D reconstruction from single view images is an ill-posed problem. Inferring the hidden regions from self-occluded images is both challenging and ambiguous. We propose a two-pronge…