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20152023
most citedDo Convolutional Neural Networks Learn Class Hierarchy?

211 citations · 665 across the 21 of their papers we have counts for

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51 papers · 1 filter

cs.CV2023

Tame a Wild Camera: In-the-Wild Monocular Camera Calibration

Shengjie Zhu, Abhinav Kumar, Masa Hu +1

3D sensing for monocular in-the-wild images, e.g., depth estimation and 3D object detection, has become increasingly important. However, the unknown intrinsic parameter hinders the…

cs.CV2023

PMatch: Paired Masked Image Modeling for Dense Geometric Matching

Shengjie Zhu, Xiaoming Liu

Dense geometric matching determines the dense pixel-wise correspondence between a source and support image corresponding to the same 3D structure. Prior works employ an encoder of…

cs.CV20211 cited

Radar-Camera Pixel Depth Association for Depth Completion

Yunfei Long, Daniel Morris, Xiaoming Liu +3

While radar and video data can be readily fused at the detection level, fusing them at the pixel level is potentially more beneficial. This is also more challenging in part due to…

cs.CV20213 cited

Riggable 3D Face Reconstruction via In-Network Optimization

Ziqian Bai, Zhaopeng Cui, Xiaoming Liu +1

This paper presents a method for riggable 3D face reconstruction from monocular images, which jointly estimates a personalized face rig and per-image parameters including expressio…

cs.CV20215 cited

Unified Detection of Digital and Physical Face Attacks

Debayan Deb, Xiaoming Liu, Anil K. Jain

State-of-the-art defense mechanisms against face attacks achieve near perfect accuracies within one of three attack categories, namely adversarial, digital manipulation, or physica…

cs.CV2021

Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction

Feng Liu, Luan Tran, Xiaoming Liu

Inferring 3D structure of a generic object from a 2D image is a long-standing objective of computer vision. Conventional approaches either learn completely from CAD-generated synth…