Join us for the Workshop on Compositional 3D Vision (C3DV) #CVPR2025! @CVPR
🏆 Challenges: https://t.co/r8Vwf76LUt
📢 Call for Papers: https://t.co/lepeqixKTp
C3DV will feature two exciting challenges and a fantastic lineup of speakers!
🧵👇
The C3DV @CVPR is starting at 8:15. Please join us,
Where: Room 110 B, Music City Center, Nashville
Zoom link is accessible through CVPR for registered participants, excellent lineup of speakers!
200+ students from across Saudi Arabia explored #AI through art, music & design at the SAAI Factory Hackathon for Kids at #KAUST.
Their projects tackled inclusion, climate change & immersive learning—blending creativity with tech.
Learn more: https://t.co/sp7uFJsT51
#ICLR 2025
🚀 Excited to share that three papers have been accepted at ICLR 2025! 🎉 Huge thanks to my incredibly talented students and collaborators for their dedication and hard work—this wouldn't have been possible without you!
@ICLR25: @KAUSTVisionCAIR’s wenxuan zhang and @ben_nebulous are presenting BFPO and Toddler diffusion this morning; posters 277 and 280 Hall 2; stop by to learn more about carefully modeling the dichotomy of safety and helpfulness and more interpretable and efficient diffusion.
Join us for the Workshop on Compositional 3D Vision (C3DV) #CVPR2025! @CVPR
🏆 Challenges: https://t.co/r8Vwf76LUt
📢 Call for Papers: https://t.co/lepeqixKTp
C3DV will feature two exciting challenges and a fantastic lineup of speakers!
🧵👇
@CVPR@HaoSuLabUCSD@tolga_birdal 🏆 We are also hosting two 3D vision challenges this year! This year's highlight: the 3DCoMPaT-200 Challenge and the Language-Based Part Grounding Challenge, focusing on 3D object composition and understanding.
📥 C3DV Challenges: https://t.co/r8Vwf76LUt
🧵 3/4
📌 Paper 3: Query-based Knowledge Transfer for Heterogeneous Learning Environments
@Norah Alballa, Wenxuan Zhang,@Ziquan Liu. Mohamed Elhoseiny. Marco Canini
✅ This paper introduces Query-based Knowledge Transfer (QKT), a novel framework for decentralized collaborative learning
📌 Paper 2: Bi-Factorial Preference Optimization (BFPO): Balancing Safety-Helpfulness in Language Models
by Wenxuan Zhang, Philip Torr, Mohamed Elhoseiny*, Adel Bibi*,
✅ BFPO is a supervised learning framework that reformulates RLHF’s joint objective of safety and helpfulness..
...into interpretable stages (e.g., contours, palettes, textures) and leverages Schrödinger Bridge optimal transport for seamless transitions between modalities, enhancing control and flexibility in the generation process.
📌 Paper 1: ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge
by Eslam Bakr, Liangbing Zhao, Tao HU, Matthieu Cord, Patrick Pérez, Mohamed Elhoseiny
✅This paper introduces a new diffusion framework that decomposes RGB image generation