63 citations · 162 across the 11 of their papers we have counts for
11 papers
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…
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…
OFFSEG: A Semantic Segmentation Framework For Off-Road Driving
Kasi Viswanath, Kartikeya Singh, Peng Jiang +2
Off-road image semantic segmentation is challenging due to the presence of uneven terrains, unstructured class boundaries, irregular features and strong textures. These aspects aff…
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…
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…
RELLIS-3D Dataset: Data, Benchmarks and Analysis
Peng Jiang, Philip Osteen, Maggie Wigness +1
Semantic scene understanding is crucial for robust and safe autonomous navigation, particularly so in off-road environments. Recent deep learning advances for 3D semantic segmentat…
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…
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…
Super Diffusion for Salient Object Detection
Peng Jiang, Zhiyi Pan, Nuno Vasconcelos +2
One major branch of saliency object detection methods is diffusion-based which construct a graph model on a given image and diffuse seed saliency values to the whole graph by a dif…
DiDA: Disentangled Synthesis for Domain Adaptation
Jinming Cao, Oren Katzir, Peng Jiang +4
Unsupervised domain adaptation aims at learning a shared model for two related, but not identical, domains by leveraging supervision from a source domain to an unsupervised target…
DifNet: Semantic Segmentation by Diffusion Networks
Peng Jiang, Fanglin Gu, Yunhai Wang +2
Deep Neural Networks (DNNs) have recently shown state of the art performance on semantic segmentation tasks, however, they still suffer from problems of poor boundary localization…