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20212024
most citedVL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic Scene Graph Prediction in Point Cloud

3 citations · 7 across the 5 of their papers we have counts for

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cs.CV2024

From Parts to Whole: A Unified Reference Framework for Controllable Human Image Generation

Zehuan Huang, Hongxing Fan, Lipeng Wang +1

Recent advancements in controllable human image generation have led to zero-shot generation using structural signals (e.g., pose, depth) or facial appearance. Yet, generating human…

cs.CV2023

Siamese DETR

Zeren Chen, Gengshi Huang, Wei Li +5

Recent self-supervised methods are mainly designed for representation learning with the base model, e.g., ResNets or ViTs. They cannot be easily transferred to DETR, with task-spec…

cs.CV20233 cited

VL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic Scene Graph Prediction in Point Cloud

Ziqin Wang, Bowen Cheng, Lichen Zhao +3

The task of 3D semantic scene graph (3DSSG) prediction in the point cloud is challenging since (1) the 3D point cloud only captures geometric structures with limited semantics comp…

cs.CV20222 cited

Improving RGB-D Point Cloud Registration by Learning Multi-scale Local Linear Transformation

Ziming Wang, Xiaoliang Huo, Zhenghao Chen +3

Point cloud registration aims at estimating the geometric transformation between two point cloud scans, in which point-wise correspondence estimation is the key to its success. In…

cs.CV20212 cited

ForgeryNet -- Face Forgery Analysis Challenge 2021: Methods and Results

Yinan He, Lu Sheng, Jing Shao +19

The rapid progress of photorealistic synthesis techniques has reached a critical point where the boundary between real and manipulated images starts to blur. Recently, a mega-scale…