2 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
MultiDiffSense: Diffusion-Based Multi-Modal Visuo-Tactile Image Generation Conditioned on Object Shape and Contact Pose
Sirine Bhouri, Lan Wei, Jian-Qing Zheng +1
Acquiring aligned visuo-tactile datasets is slow and costly, requiring specialised hardware and large-scale data collection. Synthetic generation is promising, but prior methods ar…
ProxT2I: Efficient Reward-Guided Text-to-Image Generation via Proximal Diffusion
Zhenghan Fang, Jian Zheng, Qiaozi Gao +2
Diffusion models have emerged as a dominant paradigm for generative modeling across a wide range of domains, including prompt-conditional generation. The vast majority of samplers,…
T2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design
Jiachen Li, Qian Long, Jian Zheng +4
In this paper, we focus on enhancing a diffusion-based text-to-video (T2V) model during the post-training phase by distilling a highly capable consistency model from a pretrained T…
FlexEControl: Flexible and Efficient Multimodal Control for Text-to-Image Generation
Xuehai He, Jian Zheng, Jacob Zhiyuan Fang +6
Controllable text-to-image (T2I) diffusion models generate images conditioned on both text prompts and semantic inputs of other modalities like edge maps. Nevertheless, current con…