activity
20152023
most citedDeeperGCN: All You Need to Train Deeper GCNs

260 citations · 540 across the 36 of their papers we have counts for

collaborators

77 papers

cs.CV20231 cited

Enhancing Neural Rendering Methods with Image Augmentations

Juan C. Pérez, Sara Rojas, Jesus Zarzar +1

Faithfully reconstructing 3D geometry and generating novel views of scenes are critical tasks in 3D computer vision. Despite the widespread use of image augmentations across comput…

cs.LG2022

On Robust Learning from Noisy Labels: A Permutation Layer Approach

Salman Alsubaihi, Mohammed Alkhrashi, Raied Aljadaany +2

The existence of label noise imposes significant challenges (e.g., poor generalization) on the training process of deep neural networks (DNN). As a remedy, this paper introduces a…

cs.CV20223 cited

SegNeRF: 3D Part Segmentation with Neural Radiance Fields

Jesus Zarzar, Sara Rojas, Silvio Giancola +1

Recent advances in Neural Radiance Fields (NeRF) boast impressive performances for generative tasks such as novel view synthesis and 3D reconstruction. Methods based on neural radi…

cs.CV202210 cited

Diffusion-Based Scene Graph to Image Generation with Masked Contrastive Pre-Training

Ling Yang, Zhilin Huang, Yang Song +6

Generating images from graph-structured inputs, such as scene graphs, is uniquely challenging due to the difficulty of aligning nodes and connections in graphs with objects and the…

cs.CV20221 cited

Estimating more camera poses for ego-centric videos is essential for VQ3D

Jinjie Mai, Chen Zhao, Abdullah Hamdi +2

Visual queries 3D localization (VQ3D) is a task in the Ego4D Episodic Memory Benchmark. Given an egocentric video, the goal is to answer queries of the form "Where did I last see o…

cs.CV20222 cited

Decoupled Mixup for Generalized Visual Recognition

Haozhe Liu, Wentian Zhang, Jinheng Xie +7

Convolutional neural networks (CNN) have demonstrated remarkable performance when the training and testing data are from the same distribution. However, such trained CNN models oft…