Computer Vision

SAR3D: Blazing-fast autoregressive 3D object generation and understanding using a multi-scale VQVAE, achieving sub-second generation and detailed multimodal comprehension.

Image editing is revolutionized by Frame2Frame, which uses video generation to produce seamless and accurate edits, preserving image fidelity.

OneDiffusion: A single diffusion model masters image synthesis & understanding across diverse tasks, from text-to-image to depth estimation, pushing the boundaries of AI.

Self-supervised learning of 3D representations from procedurally generated synthetic shapes achieves comparable performance to models trained on real-world datasets, highlighting the potential of synt…

FQGAN revitalizes image generation by introducing Factorized Quantization, enabling scalable and stable visual tokenization with state-of-the-art performance.

DREAMRUNNER generates high-quality storytelling videos by using LLMs for hierarchical planning, motion retrieval, and a novel spatial-temporal region-based diffusion model for fine-grained control.

BootComp: generate realistic human images wearing multiple garments using a novel synthetic data pipeline & diffusion model, enabling diverse applications like virtual try-on.

New benchmark VCT² reveals limitations of AI-generated image detectors; Visual AI Index (VAI) provides a robust evaluation framework.

MedNeXt, a novel model ensemble, optimizes brain tumor segmentation in diverse populations, achieving state-of-the-art results on the BraTS 2024 SSA and pediatric datasets.

Diptych Prompting: a novel zero-shot subject-driven image generator leveraging large-scale text-to-image models and inpainting for precise subject alignment and high-quality image synthesis.

TEXGen: A groundbreaking generative diffusion model creates high-resolution 3D mesh textures directly from text and image prompts, exceeding prior methods in quality and efficiency.

Style-friendly SNR sampler biases diffusion model training towards higher noise levels, enabling it to learn and generate images with higher style fidelity.

OminiControl: A minimal, universal framework efficiently integrates image conditions into diffusion transformers, enabling diverse and precise control over image generation.

Morph: a novel motion-free physics optimization framework drastically enhances human motion generation’s physical plausibility using synthetic data, achieving state-of-the-art quality.

Material Anything: Generate realistic materials for ANY 3D object via diffusion!

CoordTok: a novel video tokenizer drastically reduces token count for long videos, enabling memory-efficient training of diffusion models for high-quality, long video generation.

Stable Flow achieves diverse, consistent image editing without training by strategically injecting source image features into specific ‘vital’ layers of a diffusion transformer model. This training-f…

SegBook: a large-scale benchmark, reveals that fine-tuning full-body CT pre-trained models significantly improves performance on various downstream medical image segmentation tasks, particularly for s…

ViewExtrapolator leverages Stable Video Diffusion to realistically extrapolate novel views far beyond training data, dramatically improving the quality of 3D scene generation.

MyTimeMachine personalizes facial age transformation using just 50 personal photos, outperforming existing methods by generating re-aged faces that closely match a person’s actual appearance at variou…