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20182021
most citedSemCal: Semantic LiDAR-Camera Calibration using Neural MutualInformation Estimator

6 citations · 11 across the 4 of their papers we have counts for

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9 papers · 1 filter

cs.CV20216 cited

SemCal: Semantic LiDAR-Camera Calibration using Neural MutualInformation Estimator

Peng Jiang, Philip Osteen, Srikanth Saripalli

This paper proposes SemCal: an automatic, targetless, extrinsic calibration algorithm for a LiDAR and camera system using semantic information. We leverage a neural information est…

cs.CV20214 cited

Calibrating LiDAR and Camera using Semantic Mutual information

Peng Jiang, Philip Osteen, Srikanth Saripalli

We propose an algorithm for automatic, targetless, extrinsic calibration of a LiDAR and camera system using semantic information. We achieve this goal by maximizing mutual informat…

cs.CV2021

Scribble-Supervised Semantic Segmentation by Uncertainty Reduction on Neural Representation and Self-Supervision on Neural Eigenspace

Zhiyi Pan, Peng Jiang, Yunhai Wang +2

Scribble-supervised semantic segmentation has gained much attention recently for its promising performance without high-quality annotations. Due to the lack of supervision, confide…

cs.CV20201 cited

Scribble-Supervised Semantic Segmentation by Random Walk on Neural Representation and Self-Supervision on Neural Eigenspace

Zhiyi Pan, Peng Jiang, Changhe Tu

Scribble-supervised semantic segmentation has gained much attention recently for its promising performance without high-quality annotations. Many approaches have been proposed. Typ…

cs.CV2020

Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds

Guangnan Wu, Zhiyi Pan, Peng Jiang +1

Instance segmentation in point clouds is one of the most fine-grained ways to understand the 3D scene. Due to its close relationship to semantic segmentation, many works approach t…

cs.CV2020

LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation

Peng Jiang, Srikanth Saripalli

We present a boundary-aware domain adaptation model for LiDAR scan full-scene semantic segmentation (LiDARNet). Our model can extract both the domain private features and the domai…