Search Results for author: Jialian Wu

Found 6 papers, 2 papers with code

Deformable VisTR: Spatio temporal deformable attention for video instance segmentation

no code implementations12 Mar 2022 Sudhir Yarram, Jialian Wu, Pan Ji, Yi Xu, Junsong Yuan

To improve the training efficiency, we propose Deformable VisTR, leveraging spatio-temporal deformable attention module that only attends to a small fixed set of key spatio-temporal sampling points around a reference point.

Instance Segmentation Semantic Segmentation +1

Efficient Video Instance Segmentation via Tracklet Query and Proposal

no code implementations CVPR 2022 Jialian Wu, Sudhir Yarram, Hui Liang, Tian Lan, Junsong Yuan, Jayan Eledath, Gerard Medioni

In addition, VisTR is not fully end-to-end learnable in multiple video clips as it requires a hand-crafted data association to link instance tracklets between successive clips.

Instance Segmentation Semantic Segmentation +1

Stacked Homography Transformations for Multi-View Pedestrian Detection

no code implementations ICCV 2021 Liangchen Song, Jialian Wu, Ming Yang, Qian Zhang, Yuan Li, Junsong Yuan

This task is confronted with two challenges: how to establish the 3D correspondences from views to the BEV map and how to assemble occupancy information across views.

Pedestrian Detection

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation

1 code implementation13 Aug 2020 Jialian Wu, Liangchen Song, Tiancai Wang, Qian Zhang, Junsong Yuan

In the classification tree, as the number of parent class nodes are significantly less, their logits are less noisy and can be utilized to suppress the wrong/noisy logits existed in the fine-grained class nodes.

Classification Few-Shot Object Detection +5

Temporal-Context Enhanced Detection of Heavily Occluded Pedestrians

no code implementations CVPR 2020 Jialian Wu, Chunluan Zhou, Ming Yang, Qian Zhang, Yuan Li, Junsong Yuan

State-of-the-art pedestrian detectors have performed promisingly on non-occluded pedestrians, yet they are still confronted by heavy occlusions.

Pedestrian Detection

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