147 citations · 340 across the 12 of their papers we have counts for
19 papers · 1 filter
Self-supervised Amodal Video Object Segmentation
Jian Yao, Yuxin Hong, Chiyu Wang +6
Amodal perception requires inferring the full shape of an object that is partially occluded. This task is particularly challenging on two levels: (1) it requires more information t…
The Equalization Losses: Gradient-Driven Training for Long-tailed Object Recognition
Jingru Tan, Bo Li, Xin Lu +4
Long-tail distribution is widely spread in real-world applications. Due to the extremely small ratio of instances, tail categories often show inferior accuracy. In this paper, we f…
HCRF-Flow: Scene Flow from Point Clouds with Continuous High-order CRFs and Position-aware Flow Embedding
Ruibo Li, Guosheng Lin, Tong He +2
Scene flow in 3D point clouds plays an important role in understanding dynamic environments. Although significant advances have been made by deep neural networks, the performance i…
ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting
Yuliang Liu, Chunhua Shen, Lianwen Jin +4
End-to-end text-spotting, which aims to integrate detection and recognition in a unified framework, has attracted increasing attention due to its simplicity of the two complimentar…
DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic Convolution
Tong He, Chunhua Shen, Anton van den Hengel
Previous top-performing approaches for point cloud instance segmentation involve a bottom-up strategy, which often includes inefficient operations or complex pipelines, such as gro…
FCOS: A simple and strong anchor-free object detector
Zhi Tian, Chunhua Shen, Hao Chen +1
In computer vision, object detection is one of most important tasks, which underpins a few instance-level recognition tasks and many downstream applications. Recently one-stage met…