activity
20172025
most citedEmotioNet Challenge: Recognition of facial expressions of emotion in the wild

49 citations · 65 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2025

Feedback-Driven Vision-Language Alignment with Minimal Human Supervision

Giorgio Giannone, Ruoteng Li, Qianli Feng +3

Vision-language models (VLMs) have demonstrated remarkable potential in integrating visual and linguistic information, but their performance is often constrained by the need for ex…

cs.CV2022★ 7 cited

Near Perfect GAN Inversion

Qianli Feng, Viraj Shah, Raghudeep Gadde +2

To edit a real photo using Generative Adversarial Networks (GANs), we need a GAN inversion algorithm to identify the latent vector that perfectly reproduces it. Unfortunately, wher…

cs.CV2021

Diamond in the rough: Improving image realism by traversing the GAN latent space

Jeffrey Wen, Fabian Benitez-Quiroz, Qianli Feng +1

In just a few years, the photo-realism of images synthesized by Generative Adversarial Networks (GANs) has gone from somewhat reasonable to almost perfect largely by increasing the…

cs.CV2020★ 6 cited

Adding Knowledge to Unsupervised Algorithms for the Recognition of Intent

Stuart Synakowski, Qianli Feng, Aleix Martinez

Computer vision algorithms performance are near or superior to humans in the visual problems including object recognition (especially those of fine-grained categories), segmentatio…

cs.CV2017★ 49 cited

EmotioNet Challenge: Recognition of facial expressions of emotion in the wild

C. Fabian Benitez-Quiroz, Ramprakash Srinivasan, Qianli Feng +2

This paper details the methodology and results of the EmotioNet challenge. This challenge is the first to test the ability of computer vision algorithms in the automatic analysis o…