163 citations · 261 across the 5 of their papers we have counts for
9 papers
CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection
Jyh-Jing Hwang, Henrik Kretzschmar, Joshua Manela +4
Robust 3D object detection is critical for safe autonomous driving. Camera and radar sensors are synergistic as they capture complementary information and work well under different…
Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformers
Tsung-Wei Ke, Jyh-Jing Hwang, Yunhui Guo +2
Unsupervised semantic segmentation aims to discover groupings within and across images that capture object and view-invariance of a category without external supervision. Grouping…
Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Tsung-Wei Ke, Jyh-Jing Hwang, Stella X. Yu
Weakly supervised segmentation requires assigning a label to every pixel based on training instances with partial annotations such as image-level tags, object bounding boxes, label…
SegSort: Segmentation by Discriminative Sorting of Segments
Jyh-Jing Hwang, Stella X. Yu, Jianbo Shi +4
Almost all existing deep learning approaches for semantic segmentation tackle this task as a pixel-wise classification problem. Yet humans understand a scene not in terms of pixels…
DeeperLab: Single-Shot Image Parser
Tien-Ju Yang, Maxwell D. Collins, Yukun Zhu +6
We present a single-shot, bottom-up approach for whole image parsing. Whole image parsing, also known as Panoptic Segmentation, generalizes the tasks of semantic segmentation for '…
Adversarial Structure Matching for Structured Prediction Tasks
Jyh-Jing Hwang, Tsung-Wei Ke, Jianbo Shi +1
Pixel-wise losses, e.g., cross-entropy or L2, have been widely used in structured prediction tasks as a spatial extension of generic image classification or regression. However, it…