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20172023
most citedDeeperGCN: All You Need to Train Deeper GCNs

260 citations · 371 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.CV2022★ 1 cited

CLOP: Video-and-Language Pre-Training with Knowledge Regularizations

Guohao Li, Hu Yang, Feng He +4

Video-and-language pre-training has shown promising results for learning generalizable representations. Most existing approaches usually model video and text in an implicit manner,…

cs.CV2022★ 11 cited

UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance

Wei Li, Xue Xu, Xinyan Xiao +8

Diffusion generative models have recently greatly improved the power of text-conditioned image generation. Existing image generation models mainly include text conditional diffusio…

cs.CV2021★ 40 cited

ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning

Guocheng Qian, Hasan Abed Al Kader Hammoud, Guohao Li +2

Access to 3D point cloud representations has been widely facilitated by LiDAR sensors embedded in various mobile devices. This has led to an emerging need for fast and accurate poi…

cs.CV2021★ 7 cited

A CLIP-Enhanced Method for Video-Language Understanding

Guohao Li, Feng He, Zhifan Feng

This technical report summarizes our method for the Video-And-Language Understanding Evaluation (VALUE) challenge (https://value-benchmark.github.io/challenge\_2021.html). We propo…

cs.CV2020

LC-NAS: Latency Constrained Neural Architecture Search for Point Cloud Networks

Guohao Li, Mengmeng Xu, Silvio Giancola +2

Point cloud architecture design has become a crucial problem for 3D deep learning. Several efforts exist to manually design architectures with high accuracy in point cloud tasks su…

cs.CV2017★ 41 cited

Incorporating External Knowledge to Answer Open-Domain Visual Questions with Dynamic Memory Networks

Guohao Li, Hang Su, Wenwu Zhu

Visual Question Answering (VQA) has attracted much attention since it offers insight into the relationships between the multi-modal analysis of images and natural language. Most of…