1 citations · 1 across the 10 of their papers we have counts for
12 papers
UltraFlash: Accelerating Megapixel Visual Synthesis
Phuc Lai, Anh Nguyen, Phong Nguyen +1
Megapixel visual synthesis with latent diffusion models requires operating far beyond the resolutions at which these models are typically trained. Cascade refinement is a leading s…
Recency Forcing: Bridging the Long-Horizon Gap in Autoregressive Video Generation
Tri Cao, Hung Nguyen, Phong Nguyen +1
Autoregressive (AR) video generation degrades over long horizons due to an overlooked train-inference discrepancy we term KV eviction mismatch: models train on short clips where al…
Cross-Space Distillation: Teaching One-Step Students with Modern Diffusion Teachers
Anh Nguyen, Ngan Nguyen, Duc Vu +11
Modern one-step diffusion models achieve impressive quality through distribution-based timestep distillation. Yet, they rely on a critical assumption: Teacher and Student must inha…
Alice v1: Distillation-Enhanced Video Generation Surpassing Closed-Source Models
Wang Xiaoyu, Phong Nguyen, Chen Zhao
Wepresent Alice v1, a 14-billion parameter open-source video generation model that achieves state-of-the-art quality through consistency distillation with score regularization (rCM…
SwiftTailor: Efficient 3D Garment Generation with Geometry Image Representation
Phuc Pham, Uy Dieu Tran, Binh-Son Hua +1
Realistic and efficient 3D garment generation remains a longstanding challenge in computer vision and digital fashion. Existing methods typically rely on large vision- language mod…
InverFill: One-Step Inversion for Enhanced Few-Step Diffusion Inpainting
Duc Vu, Kien Nguyen, Trong-Tung Nguyen +5
Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-to-image models offer faster generatio…
PixelRush: Ultra-Fast, Training-Free High-Resolution Image Generation via One-step Diffusion
Hong-Phuc Lai, Phong Nguyen, Anh Tran
Pre-trained diffusion models excel at generating high-quality images but remain inherently limited by their native training resolution. Recent training-free approaches have attempt…
Ar2Can: An Architect and an Artist Leveraging a Canvas for Multi-Human Generation
Shubhankar Borse, Phuc Pham, Farzad Farhadzadeh +6
Despite recent advances in personalized image generation, existing models consistently fail to produce reliable multi-human scenes, often merging or losing facial identity. We pres…
SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation
Duc-Hai Pham, Tung Do, Phong Nguyen +3
We propose SharpDepth, a novel approach to monocular metric depth estimation that combines the metric accuracy of discriminative depth estimation methods (e.g., Metric3D, UniDepth)…
ModeDreamer: Mode Guiding Score Distillation for Text-to-3D Generation using Reference Image Prompts
Uy Dieu Tran, Minh Luu, Phong Ha Nguyen +2
Existing Score Distillation Sampling (SDS)-based methods have driven significant progress in text-to-3D generation. However, 3D models produced by SDS-based methods tend to exhibit…
Semi-supervised 3D Semantic Scene Completion with 2D Vision Foundation Model Guidance
Duc-Hai Pham, Duc-Dung Nguyen, Anh Pham +4
Accurate prediction of 3D semantic occupancy from 2D visual images is vital in enabling autonomous agents to comprehend their surroundings for planning and navigation. State-of-the…
DiverseDream: Diverse Text-to-3D Synthesis with Augmented Text Embedding
Uy Dieu Tran, Minh Luu, Phong Ha Nguyen +2
Text-to-3D synthesis has recently emerged as a new approach to sampling 3D models by adopting pretrained text-to-image models as guiding visual priors. An intriguing but underexplo…