Search Results for author: Anlin Zheng

Found 7 papers, 3 papers with code

Detection in Crowded Scenes: One Proposal, Multiple Predictions

3 code implementations CVPR 2020 Xuangeng Chu, Anlin Zheng, Xiangyu Zhang, Jian Sun

We propose a simple yet effective proposal-based object detector, aiming at detecting highly-overlapped instances in crowded scenes.

Object Detection Pedestrian Detection

Self-Supervised Visual Representation Learning with Semantic Grouping

1 code implementation30 May 2022 Xin Wen, Bingchen Zhao, Anlin Zheng, Xiangyu Zhang, Xiaojuan Qi

The semantic grouping is performed by assigning pixels to a set of learnable prototypes, which can adapt to each sample by attentive pooling over the feature and form new slots.

Contrastive Learning Instance Segmentation +6

Complementary Segmentation of Primary Video Objects with Reversible Flows

no code implementations23 Nov 2018 Jia Li, Junjie Wu, Anlin Zheng, Yafei Song, Yu Zhang, Xiaowu Chen

Segmenting primary objects in a video is an important yet challenging problem in computer vision, as it exhibits various levels of foreground/background ambiguities.

Superpixels Video Semantic Segmentation

Look, Perceive and Segment: Finding the Salient Objects in Images via Two-Stream Fixation-Semantic CNNs

no code implementations ICCV 2017 Xiaowu Chen, Anlin Zheng, Jia Li, Feng Lu

Toward this end, this paper proposes two-stream fixation-semantic CNNs, whose architecture is inspired by the fact that salient objects in complex images can be unambiguously annotated by selecting the pre-segmented semantic objects that receive the highest fixation density in eye-tracking experiments.

object-detection RGB Salient Object Detection +1

Primary Video Object Segmentation via Complementary CNNs and Neighborhood Reversible Flow

no code implementations ICCV 2017 Jia Li, Anlin Zheng, Xiaowu Chen, Bin Zhou

By applying CCNN on each video frame, the spatial foregroundness and backgroundness maps can be initialized, which are then propagated between various frames so as to segment primary video objects and suppress distractors.

Semantic Segmentation Superpixels +2

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