Search Results for author: Guocheng Qian

Found 17 papers, 11 papers with code

GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering

1 code implementation15 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%.

3D Reconstruction Novel View Synthesis

Dr$^2$Net: Dynamic Reversible Dual-Residual Networks for Memory-Efficient Finetuning

1 code implementation8 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.

object-detection Small Object Detection +1

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

1 code implementation30 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.

Image to 3D

Exploring Open-Vocabulary Semantic Segmentation without Human Labels

no code implementations1 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.

Open Vocabulary Semantic Segmentation Segmentation +3

LLM as A Robotic Brain: Unifying Egocentric Memory and Control

no code implementations19 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.

Embodied Question Answering Language Modelling +2

Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding

1 code implementation25 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.

3D Point Cloud Classification Inductive Bias +2

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

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.

3D Part Segmentation 3D Point Cloud Classification +2

DeepGCNs: Making GCNs Go as Deep as CNNs

4 code implementations15 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.

3D Point Cloud Classification 3D Semantic Segmentation +2

Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline

1 code implementation7 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.

Demosaicking Denoising +1

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