1 code implementation • 15 Feb 2024 • Abdullah Hamdi, Luke Melas-Kyriazi, Guocheng Qian, Jinjie Mai, Ruoshi Liu, Carl Vondrick, Bernard Ghanem, Andrea Vedaldi
With the aid of a frequency-modulated loss, GES achieves competitive performance in novel-view synthesis benchmarks while requiring less than half the memory storage of Gaussian Splatting and increasing the rendering speed by up to 39%.
no code implementations • 7 Feb 2024 • Yash Kant, Ziyi Wu, Michael Vasilkovsky, Guocheng Qian, Jian Ren, Riza Alp Guler, Bernard Ghanem, Sergey Tulyakov, Igor Gilitschenski, Aliaksandr Siarohin
We present SPAD, a novel approach for creating consistent multi-view images from text prompts or single images.
no code implementations • 1 Feb 2024 • Guocheng Qian, Junli Cao, Aliaksandr Siarohin, Yash Kant, Chaoyang Wang, Michael Vasilkovsky, Hsin-Ying Lee, Yuwei Fang, Ivan Skorokhodov, Peiye Zhuang, Igor Gilitschenski, Jian Ren, Bernard Ghanem, Kfir Aberman, Sergey Tulyakov
We introduce Amortized Text-to-Mesh (AToM), a feed-forward text-to-mesh framework optimized across multiple text prompts simultaneously.
no code implementations • 10 Jan 2024 • Chaoyang Wang, Peiye Zhuang, Aliaksandr Siarohin, Junli Cao, Guocheng Qian, Hsin-Ying Lee, Sergey Tulyakov
Dynamic novel view synthesis aims to capture the temporal evolution of visual content within videos.
1 code implementation • 8 Jan 2024 • Chen Zhao, Shuming Liu, Karttikeya Mangalam, Guocheng Qian, Fatimah Zohra, Abdulmohsen Alghannam, Jitendra Malik, Bernard Ghanem
We use two coefficients on either type of residual connections respectively, and introduce a dynamic training strategy that seamlessly transitions the pretrained model to a reversible network with much higher numerical precision.
1 code implementation • 30 Jun 2023 • Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, Bernard Ghanem
We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors.
no code implementations • 1 Jun 2023 • Jun Chen, Deyao Zhu, Guocheng Qian, Bernard Ghanem, Zhicheng Yan, Chenchen Zhu, Fanyi Xiao, Mohamed Elhoseiny, Sean Chang Culatana
Although acquired extensive knowledge of visual concepts, it is non-trivial to exploit knowledge from these VL models to the task of semantic segmentation, as they are usually trained at an image level.
no code implementations • 19 Apr 2023 • Jinjie Mai, Jun Chen, Bing Li, Guocheng Qian, Mohamed Elhoseiny, Bernard Ghanem
In this paper, we propose a novel and generalizable framework called LLM-Brain: using Large-scale Language Model as a robotic brain to unify egocentric memory and control.
no code implementations • ICCV 2023 • Jun Chen, Deyao Zhu, Guocheng Qian, Bernard Ghanem, Zhicheng Yan, Chenchen Zhu, Fanyi Xiao, Sean Chang Culatana, Mohamed Elhoseiny
Semantic segmentation is a crucial task in computer vision that involves segmenting images into semantically meaningful regions at the pixel level.
1 code implementation • 25 Aug 2022 • Guocheng Qian, Abdullah Hamdi, Xingdi Zhang, Bernard Ghanem
Pretrained on a large number of widely available images, significant gains of PViT are observed in the tasks of 3D point cloud classification, part segmentation, and semantic segmentation on ScanObjectNN, ShapeNetPart, and S3DIS, respectively.
3 code implementations • 9 Jun 2022 • Guocheng Qian, Yuchen Li, Houwen Peng, Jinjie Mai, Hasan Abed Al Kader Hammoud, Mohamed Elhoseiny, Bernard Ghanem
In this work, we revisit the classical PointNet++ through a systematic study of model training and scaling strategies, and offer two major contributions.
Ranked #3 on 3D Semantic Segmentation on OpenTrench3D
1 code implementation • 11 Apr 2022 • Guocheng Qian, Xuanyang Zhang, Guohao Li, Chen Zhao, Yukang Chen, Xiangyu Zhang, Bernard Ghanem, Jian Sun
TNAS performs a modified bi-level Breadth-First Search in the proposed trees to discover a high-performance architecture.
1 code implementation • NeurIPS 2021 • Guocheng Qian, Hasan Abed Al Kader Hammoud, Guohao Li, Ali Thabet, Bernard Ghanem
We then introduce a new Anisotropic Reduction function into our Separable SA module and propose an Anisotropic Separable SA (ASSA) module that substantially increases the network's accuracy.
Ranked #33 on 3D Part Segmentation on ShapeNet-Part
1 code implementation • CVPR 2021 • Guocheng Qian, Abdulellah Abualshour, Guohao Li, Ali Thabet, Bernard Ghanem
We combine Inception DenseGCN with NodeShuffle into a new point upsampling pipeline called PU-GCN.
1 code implementation • CVPR 2020 • Guohao Li, Guocheng Qian, Itzel C. Delgadillo, Matthias Müller, Ali Thabet, Bernard Ghanem
Architecture design has become a crucial component of successful deep learning.
Ranked #4 on Node Classification on PPI
4 code implementations • 15 Oct 2019 • Guohao Li, Matthias Müller, Guocheng Qian, Itzel C. Delgadillo, Abdulellah Abualshour, Ali Thabet, Bernard Ghanem
This work transfers concepts such as residual/dense connections and dilated convolutions from CNNs to GCNs in order to successfully train very deep GCNs.
Ranked #5 on 3D Semantic Segmentation on PartNet
1 code implementation • 7 May 2019 • Guocheng Qian, Yuanhao Wang, Jinjin Gu, Chao Dong, Wolfgang Heidrich, Bernard Ghanem, Jimmy S. Ren
In this work, we comprehensively study the effects of pipelines on the mixture problem of learning-based DN, DM, and SR, in both sequential and joint solutions.