29 citations · 53 across the 5 of their papers we have counts for
9 papers
im2nerf: Image to Neural Radiance Field in the Wild
Lu Mi, Abhijit Kundu, David Ross +3
We propose im2nerf, a learning framework that predicts a continuous neural object representation given a single input image in the wild, supervised by only segmentation output from…
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation
Abhijit Kundu, Kyle Genova, Xiaoqi Yin +6
We present Panoptic Neural Fields (PNF), an object-aware neural scene representation that decomposes a scene into a set of objects (things) and background (stuff). Each object is r…
Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer +32
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and trainin…
Learning 3D Semantic Segmentation with only 2D Image Supervision
Kyle Genova, Xiaoqi Yin, Abhijit Kundu +6
With the recent growth of urban mapping and autonomous driving efforts, there has been an explosion of raw 3D data collected from terrestrial platforms with lidar scanners and colo…
Virtual Multi-view Fusion for 3D Semantic Segmentation
Abhijit Kundu, Xiaoqi Yin, Alireza Fathi +4
Semantic segmentation of 3D meshes is an important problem for 3D scene understanding. In this paper we revisit the classic multiview representation of 3D meshes and study several…
Pillar-based Object Detection for Autonomous Driving
Yue Wang, Alireza Fathi, Abhijit Kundu +4
We present a simple and flexible object detection framework optimized for autonomous driving. Building on the observation that point clouds in this application are extremely sparse…