ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2011.07466
  4. Cited By
Continuous Conditional Generative Adversarial Networks: Novel Empirical
  Losses and Label Input Mechanisms

Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms

15 November 2020
Xin Ding
Student Member Ieee Yongwei Wang
Zuheng Xu
William J. Welch
F. I. Z. Jane Wang
    GAN
    VLM
ArXivPDFHTML

Papers citing "Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms"

3 / 3 papers shown
Title
Synthesizing Forestry Images Conditioned on Plant Phenotype Using a Generative Adversarial Network
Synthesizing Forestry Images Conditioned on Plant Phenotype Using a Generative Adversarial Network
Debasmita Pal
Arun Ross
GAN
79
1
0
17 Jan 2025
CCDM: Continuous Conditional Diffusion Models for Image Generation
CCDM: Continuous Conditional Diffusion Models for Image Generation
Xin Ding
Member Ieee Yongwei Wang
Kao Zhang
F. I. Z. Jane Wang
DiffM
16
3
0
06 May 2024
Conditional Image Synthesis With Auxiliary Classifier GANs
Conditional Image Synthesis With Auxiliary Classifier GANs
Augustus Odena
C. Olah
Jonathon Shlens
GAN
224
3,185
0
30 Oct 2016
1