Search papers, labs, and topics across Lattice.
A pathwise approach to change detection reveals that continuous transport in feature space significantly enhances the model's ability to capture and interpret temporal changes.
AugSplat boosts reconstruction quality in sparse-view 3D vision by leveraging synthetic views from neural radiance fields, achieving real-time performance without sacrificing accuracy.
LiDAR-based 3D object detectors can be compromised by targeting just a few critical spatial regions, revealing a significant structural vulnerability.
Triangle splats from video diffusion latents yield superior geometric accuracy and visual quality, challenging the dominance of volumetric 3D Gaussians in scene generation.
Ditch the brittle code synthesis and noisy gradients: LiveSVG unlocks high-quality SVG animations by directly fitting vector graphics to reference videos generated from motion prompts.
Imagine telepresence where your avatar convincingly blends into any environment, relit in real-time based on the scene's actual lighting, all from a single headset.
You can slash the compute cost of visual geometry transformers by 85% without sacrificing accuracy by intelligently pruning redundant tokens across frames and within layers.
Forget handcrafted prompts: a hierarchical multi-agent framework turns diffusion models into coherent storytelling engines by globally optimizing for semantic coherence.
Current remote sensing change captioning datasets miss fine-grained localized semantic reasoning, but RSRCC fills this gap with 126k change-specific questions.
LVLMs can self-detect and correct object hallucinations by focusing on specific image regions, offering a simple, training-free fix.
Generating consistent visual narratives is now possible: CANVAS outperforms existing methods by explicitly planning character, background, and scene continuity across multiple shots.
Reconstructing dynamic hand-object interactions from monocular video can be 6x faster and significantly more accurate by ditching heavy neural representations for a revived Sum-of-Gaussians approach.
Achieve world-consistent video generation by directly optimizing geometry in the latent space of pre-trained video diffusion models, sidestepping costly RGB-space operations and architectural changes.
Imagine an XR experience where you can selectively isolate and enhance individual sound sources in real-time, making chaotic audio environments crystal clear.
Forget local semantic alignment: CAST unlocks temporally coherent video retrieval and generation by explicitly modeling visual state transitions.
AI-generated videos can now respect physics, thanks to a framework that uses a physical simulator to guide diffusion models, resulting in more realistic and coherent motion.
Existing deforestation monitoring maps misclassify smallholder agroforestry as "forest," risking unfair penalties under regulations like the EUDR.
Forget complex architectures: RaCo achieves SOTA keypoint matching and repeatability by cleverly combining ranking and covariance estimation in a lightweight network, trained without covisible image pairs.
