37 citations · 69 across the 19 of their papers we have counts for
6 papers · 1 filter
BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion
Jinheng Xie, Yuexiang Li, Yawen Huang +4
Recent text-to-image diffusion models have demonstrated an astonishing capacity to generate high-quality images. However, researchers mainly studied the way of synthesizing images…
Learning to Identify Critical States for Reinforcement Learning from Videos
Haozhe Liu, Mingchen Zhuge, Bing Li +4
Recent work on deep reinforcement learning (DRL) has pointed out that algorithmic information about good policies can be extracted from offline data which lack explicit information…
Dynamically Masked Discriminator for Generative Adversarial Networks
Wentian Zhang, Haozhe Liu, Bing Li +5
Training Generative Adversarial Networks (GANs) remains a challenging problem. The discriminator trains the generator by learning the distribution of real/generated data. However,…
Mindstorms in Natural Language-Based Societies of Mind
Mingchen Zhuge, Haozhe Liu, Francesco Faccio +23
Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each o…
Open-World Weakly-Supervised Object Localization
Jinheng Xie, Zhaochuan Luo, Yuexiang Li +3
While remarkable success has been achieved in weakly-supervised object localization (WSOL), current frameworks are not capable of locating objects of novel categories in open-world…
Improving GAN Training via Feature Space Shrinkage
Haozhe Liu, Wentian Zhang, Bing Li +6
Due to the outstanding capability for data generation, Generative Adversarial Networks (GANs) have attracted considerable attention in unsupervised learning. However, training GANs…