Search Results for author:
Found 8 papers, 6 papers with code
Open-Pose 3D Zero-Shot Learning: Benchmark and Challenges
To this end, we propose a more realistic and challenging scenario named open-pose 3D zero-shot classification, focusing on the recognition of 3D objects regardless of their orientation.
Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation
On the one hand, the unidirectional projection enforces our model focused more on the core task, i. e., 3D segmentation; on the other hand, unlocking the bidirectional to unidirectional projection enables a deeper cross-domain semantic alignment and enjoys the flexibility to fuse better and complicated features from very different spaces.
SSD: Towards Better Text-Image Consistency Metric in Text-to-Image Generation
Generating consistent and high-quality images from given texts is essential for visual-language understanding.
Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization
Due to the uneven distribution of offset points, these existing methods can hardly cluster all instance points.
Ranked #3 on
3D Instance Segmentation
on S3DIS
3D Random Occlusion and Multi-Layer Projection for Deep Multi-Camera Pedestrian Localization
Although deep-learning based methods for monocular pedestrian detection have made great progress, they are still vulnerable to heavy occlusions.
Ranked #2 on
Multiview Detection
on Wildtrack
(using extra training data)
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation
This combination of global and local alignment can precisely localize the crucial regions in segmentation target while preserving the overall semantic consistency.
From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion
While weakly supervised multi-view face reconstruction (MVR) is garnering increased attention, one critical issue still remains open: how to effectively fuse multiple image information to reconstruct high-precision 3D models.
Generalised Image Outpainting with U-Transformer
In this paper, we develop a novel transformer-based generative adversarial neural network called U-Transformer for generalised image outpainting problem.
