Computer Vision

Unified 3D latent representation (SLAT) enables versatile high-quality 3D asset generation, significantly outperforming existing methods.

PhysGame benchmark unveils video LLMs’ weaknesses in understanding physical commonsense from gameplay videos, prompting the creation of PhysVLM, a knowledge-enhanced model that outperforms existing mo…

One-shot image to realistic, animatable talking avatar! Novel pipeline uses diffusion models and a hybrid 3DGS-mesh representation, achieving seamless generalization and precise control.

NitroFusion achieves high-fidelity single-step image generation using a dynamic adversarial training approach with a specialized discriminator pool, dramatically improving speed and quality.

NegToMe: Image-based adversarial guidance improves image generation diversity and reduces similarity to copyrighted content without training, simply by using images instead of negative text prompts.

Presto: a novel video diffusion model generates 15-second, high-quality videos with unparalleled long-range coherence and rich content, achieved through a segmented cross-attention mechanism and the L…

VISTA synthesizes long-duration, high-resolution video instruction data, creating VISTA-400K and HRVideoBench to significantly boost video LMM performance.

DisCoRD: Rectified flow decodes discrete motion tokens into continuous, natural movement, balancing faithfulness and realism.

AlphaTablets: A novel 3D plane representation enabling accurate, consistent, and flexible 3D planar reconstruction from monocular videos, achieving state-of-the-art results.

RollingDepth: Achieving state-of-the-art video depth estimation without using complex video models, by cleverly extending a single-image depth estimator.

Trajectory Attention enhances video motion control by injecting trajectory information, improving precision and long-range consistency in video generation.

TeaCache: a training-free method boosts video diffusion model speed by up to 4.41x with minimal quality loss by cleverly caching intermediate outputs.

Open-Sora Plan introduces an open-source large video generation model capable of producing high-resolution videos with long durations, based on various user inputs.

EfficientTAMs achieve comparable video object segmentation accuracy to SAM 2 with ~2x speedup using lightweight ViTs and efficient cross-attention.

TryOffDiff generates realistic garment images from single photos, solving virtual try-on limitations.

TAPTRv3 achieves state-of-the-art long-video point tracking by cleverly using spatial and temporal context to enhance feature querying, surpassing previous methods and demonstrating strong performance…

ROICtrl boosts visual generation’s instance control by using regional instance control via ROI-Align and a new ROI-Unpool operation, resulting in precise regional control and high efficiency.

Make-It-Animatable: Instantly create animation-ready 3D characters, regardless of pose or shape, using a novel data-driven framework.

FAM Diffusion: Generate high-res images seamlessly from pre-trained diffusion models, solving structural and texture inconsistencies without retraining!

CAT4D: Create realistic 4D scenes from single-view videos using a novel multi-view video diffusion model.