2 citations · 4 across the 6 of their papers we have counts for
6 papers
MCTformer+: Multi-Class Token Transformer for Weakly Supervised Semantic Segmentation
Lian Xu, Mohammed Bennamoun, Farid Boussaid +3
This paper proposes a novel transformer-based framework that aims to enhance weakly supervised semantic segmentation (WSSS) by generating accurate class-specific object localizatio…
Learning Unified Decompositional and Compositional NeRF for Editable Novel View Synthesis
Yuxin Wang, Wayne Wu, Dan Xu
Implicit neural representations have shown powerful capacity in modeling real-world 3D scenes, offering superior performance in novel view synthesis. In this paper, we target a mor…
TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-Experts
Hanrong Ye, Dan Xu
Learning discriminative task-specific features simultaneously for multiple distinct tasks is a fundamental problem in multi-task learning. Recent state-of-the-art models consider d…
Contrastive Multi-Task Dense Prediction
Siwei Yang, Hanrong Ye, Dan Xu
This paper targets the problem of multi-task dense prediction which aims to achieve simultaneous learning and inference on a bunch of multiple dense prediction tasks in a single fr…
InvPT++: Inverted Pyramid Multi-Task Transformer for Visual Scene Understanding
Hanrong Ye, Dan Xu
Multi-task scene understanding aims to design models that can simultaneously predict several scene understanding tasks with one versatile model. Previous studies typically process…
Joint 2D-3D Multi-Task Learning on Cityscapes-3D: 3D Detection, Segmentation, and Depth Estimation
Hanrong Ye, Dan Xu
This report serves as a supplementary document for TaskPrompter, detailing its implementation on a new joint 2D-3D multi-task learning benchmark based on Cityscapes-3D. TaskPrompte…