most citedRodinHD: High-Fidelity 3D Avatar Generation with Diffusion Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

MorphoQuant: Modality-Aware Quantization for Omni-modal Large Language Models

Yue Wu, Changyuan Wang, Zixuan Wang +2

Conventional Post-Training Quantization (PTQ) methods struggle with 4-bit Omni-modal Large Language Models (OLLMs) due to the extreme distribution heterogeneity and disparate outli…

cs.CV2026

Meta-CoT: Enhancing Granularity and Generalization in Image Editing

Shiyi Zhang, Yiji Cheng, Tiankai Hang +8

Unified multi-modal understanding/generative models have shown improved image editing performance by incorporating fine-grained understanding into their Chain-of-Thought (CoT) proc…

cs.CV2026

ChatUMM: Robust Context Tracking for Conversational Interleaved Generation

Wenxun Dai, Zhiyuan Zhao, Yule Zhong +12

Unified multimodal models (UMMs) have achieved remarkable progress yet remain constrained by a single-turn interaction paradigm, effectively functioning as solvers for independent…

cs.CV20241 cited

RodinHD: High-Fidelity 3D Avatar Generation with Diffusion Models

Bowen Zhang, Yiji Cheng, Chunyu Wang +6

We present RodinHD, which can generate high-fidelity 3D avatars from a portrait image. Existing methods fail to capture intricate details such as hairstyles which we tackle in this…

cs.RO2024

ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation

Zifeng Gao, Guanxing Lu, Tianxing Chen +5

Diffusion models have been verified to be effective in generating complex distributions from natural images to motion trajectories. Recent diffusion-based methods show impressive p…