27 citations · 54 across the 8 of their papers we have counts for
11 papers · 1 filter
Semantic Segmentation by Early Region Proxy
Yifan Zhang, Bo Pang, Cewu Lu
Typical vision backbones manipulate structured features. As a compromise, semantic segmentation has long been modeled as per-point prediction on dense regular grids. In this work,…
PGT: A Progressive Method for Training Models on Long Videos
Bo Pang, Gao Peng, Yizhuo Li +1
Convolutional video models have an order of magnitude larger computational complexity than their counterpart image-level models. Constrained by computational resources, there is no…
TDAF: Top-Down Attention Framework for Vision Tasks
Bo Pang, Yizhuo Li, Jiefeng Li +3
Human attention mechanisms often work in a top-down manner, yet it is not well explored in vision research. Here, we propose the Top-Down Attention Framework (TDAF) to capture top-…
ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation
Hanwen Cao, Yongyi Lu, Cewu Lu +3
Recent works of point clouds show that mulit-frame spatio-temporal modeling outperforms single-frame versions by utilizing cross-frame information. In this paper, we further improv…
TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model
Bo Pang, Yizhuo Li, Yifan Zhang +2
Multi-object tracking is a fundamental vision problem that has been studied for a long time. As deep learning brings excellent performances to object detection algorithms, Tracking…
Complex Sequential Understanding through the Awareness of Spatial and Temporal Concepts
Bo Pang, Kaiwen Zha, Hanwen Cao +3
Understanding sequential information is a fundamental task for artificial intelligence. Current neural networks attempt to learn spatial and temporal information as a whole, limite…