Search Results for author: Chaoxu Guo

Found 8 papers, 5 papers with code

Hierarchical Masked 3D Diffusion Model for Video Outpainting

no code implementations5 Sep 2023 Fanda Fan, Chaoxu Guo, Litong Gong, Biao Wang, Tiezheng Ge, Yuning Jiang, Chunjie Luo, Jianfeng Zhan

Our pipeline benefits from bidirectional learning of the mask modeling and thus can employ a hybrid strategy of infilling and interpolation when generating sparse frames.

Image Outpainting

Estimation of Reliable Proposal Quality for Temporal Action Detection

1 code implementation25 Apr 2022 Junshan Hu, Chaoxu Guo, Liansheng Zhuang, Biao Wang, Tiezheng Ge, Yuning Jiang, Houqiang Li

For the region perspective, we introduce Region Evaluate Module (REM) which uses a new and efficient sampling method for proposal feature representation containing more contextual information compared with point feature to refine category score and proposal boundary.

Action Detection

PV-RCNN: The Top-Performing LiDAR-only Solutions for 3D Detection / 3D Tracking / Domain Adaptation of Waymo Open Dataset Challenges

1 code implementation28 Aug 2020 Shaoshuai Shi, Chaoxu Guo, Jihan Yang, Hongsheng Li

In this technical report, we present the top-performing LiDAR-only solutions for 3D detection, 3D tracking and domain adaptation three tracks in Waymo Open Dataset Challenges 2020.

3D Object Detection Domain Adaptation +1

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

12 code implementations CVPR 2020 Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, Hongsheng Li

We present a novel and high-performance 3D object detection framework, named PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds.

Object object-detection +1

AugFPN: Improving Multi-scale Feature Learning for Object Detection

2 code implementations CVPR 2020 Chaoxu Guo, Bin Fan, Qian Zhang, Shiming Xiang, Chunhong Pan

In this paper, we begin by first analyzing the design defects of feature pyramid in FPN, and then introduce a new feature pyramid architecture named AugFPN to address these problems.

Object object-detection +1

Progressive Sparse Local Attention for Video object detection

no code implementations ICCV 2019 Chaoxu Guo, Bin Fan, Jie Gu, Qian Zhang, Shiming Xiang, Veronique Prinet, Chunhong Pan

Instead of relying on optical flow, this paper proposes a novel module called Progressive Sparse Local Attention (PSLA), which establishes the spatial correspondence between features across frames in a local region with progressively sparser stride and uses the correspondence to propagate features.

Object object-detection +2

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