1 citations · 4 across the 6 of their papers we have counts for
6 papers
Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance
Kuan Heng Lin, Sicheng Mo, Ben Klingher +2
Recent controllable generation approaches such as FreeControl and Diffusion Self-Guidance bring fine-grained spatial and appearance control to text-to-image (T2I) diffusion models…
SnAG: Scalable and Accurate Video Grounding
Fangzhou Mu, Sicheng Mo, Yin Li
Temporal grounding of text descriptions in videos is a central problem in vision-language learning and video understanding. Existing methods often prioritize accuracy over scalabil…
FreeControl: Training-Free Spatial Control of Any Text-to-Image Diffusion Model with Any Condition
Sicheng Mo, Fangzhou Mu, Kuan Heng Lin +4
Recent approaches such as ControlNet offer users fine-grained spatial control over text-to-image (T2I) diffusion models. However, auxiliary modules have to be trained for each type…
Where a Strong Backbone Meets Strong Features -- ActionFormer for Ego4D Moment Queries Challenge
Fangzhou Mu, Sicheng Mo, Gillian Wang +1
This report describes our submission to the Ego4D Moment Queries Challenge 2022. Our submission builds on ActionFormer, the state-of-the-art backbone for temporal action localizati…
A Simple Transformer-Based Model for Ego4D Natural Language Queries Challenge
Sicheng Mo, Fangzhou Mu, Yin Li
This report describes Badgers@UW-Madison, our submission to the Ego4D Natural Language Queries (NLQ) Challenge. Our solution inherits the point-based event representation from our…
Physics to the Rescue: Deep Non-line-of-sight Reconstruction for High-speed Imaging
Fangzhou Mu, Sicheng Mo, Jiayong Peng +5
Computational approach to imaging around the corner, or non-line-of-sight (NLOS) imaging, is becoming a reality thanks to major advances in imaging hardware and reconstruction algo…