most citedRepPoints V2: Verification Meets Regression for Object Detection

70 citations · 90 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV202070 cited

RepPoints V2: Verification Meets Regression for Object Detection

Yihong Chen, Zheng Zhang, Yue Cao +3

Verification and regression are two general methodologies for prediction in neural networks. Each has its own strengths: verification can be easier to infer accurately, and regress…

cs.CV20206 cited

Multi-modal Feature Fusion with Feature Attention for VATEX Captioning Challenge 2020

Ke Lin, Zhuoxin Gan, Liwei Wang

This report describes our model for VATEX Captioning Challenge 2020. First, to gather information from multiple domains, we extract motion, appearance, semantic and audio features.…

cs.CL202012 cited

MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning

Jie Lei, Liwei Wang, Yelong Shen +3

Generating multi-sentence descriptions for videos is one of the most challenging captioning tasks due to its high requirements for not only visual relevance but also discourse-base…

cs.CV2019

Dense RepPoints: Representing Visual Objects with Dense Point Sets

Ze Yang, Yinghao Xu, Han Xue +5

We present a new object representation, called Dense RepPoints, that utilizes a large set of points to describe an object at multiple levels, including both box level and pixel lev…

cs.CV2019

A Fast and Accurate One-Stage Approach to Visual Grounding

Zhengyuan Yang, Boqing Gong, Liwei Wang +3

We propose a simple, fast, and accurate one-stage approach to visual grounding, inspired by the following insight. The performances of existing propose-and-rank two-stage methods a…

cs.CV20192 cited

Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing

Jun Gao, Xiao Li, Liwei Wang +2

We present a method for compositing virtual objects into a photograph such that the object colors appear to have been processed by the photo's camera imaging pipeline. Compositing…