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20222024
most citedMulti-direction and Multi-scale Pyramid in Transformer for Video-based Pedestrian Retrieval

99 citations · 104 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024

EPContrast: Effective Point-level Contrastive Learning for Large-scale Point Cloud Understanding

Zhiyi Pan, Guoqing Liu, Wei Gao +1

The acquisition of inductive bias through point-level contrastive learning holds paramount significance in point cloud pre-training. However, the square growth in computational req…

cs.CV2024

Distribution Guidance Network for Weakly Supervised Point Cloud Semantic Segmentation

Zhiyi Pan, Wei Gao, Shan Liu +1

Despite alleviating the dependence on dense annotations inherent to fully supervised methods, weakly supervised point cloud semantic segmentation suffers from inadequate supervisio…

cs.CV2023

Mug-STAN: Adapting Image-Language Pretrained Models for General Video Understanding

Ruyang Liu, Jingjia Huang, Wei Gao +2

Large-scale image-language pretrained models, e.g., CLIP, have demonstrated remarkable proficiency in acquiring general multi-modal knowledge through web-scale image-text data. Des…

cs.CV2022

Deep Geometry Post-Processing for Decompressed Point Clouds

Xiaoqing Fan, Ge Li, Dingquan Li +3

Point cloud compression plays a crucial role in reducing the huge cost of data storage and transmission. However, distortions can be introduced into the decompressed point clouds d…

cs.CV20225 cited

Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation

Wenbo Zhao, Xianming Liu, Zhiwei Zhong +4

Point clouds upsampling is a challenging issue to generate dense and uniform point clouds from the given sparse input. Most existing methods either take the end-to-end supervised l…

cs.CV202299 cited

Multi-direction and Multi-scale Pyramid in Transformer for Video-based Pedestrian Retrieval

Xianghao Zang, Ge Li, Wei Gao

In video surveillance, pedestrian retrieval (also called person re-identification) is a critical task. This task aims to retrieve the pedestrian of interest from non-overlapping ca…