1 citations · 1 across the 13 of their papers we have counts for
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AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers
Javad Rajabi, Koorosh Roohi, David B. Lindell +1
Generating images beyond the training resolution of Diffusion Transformers (DiTs) remains challenging, as the number of tokens grows rapidly with resolution, full attention becomes…
ProxyPose: 6-DoF Pose Tracking via Video-to-Video Translation
Ruihang Zhang, Felix Taubner, Pooja Ravi +2
Tracking the six-degree-of-freedom (6-DoF) pose of objects and surfaces from monocular video is a long-standing problem in computer vision. To tackle this problem, existing methods…
REALM: An RGB- and Event-Aligned Latent Manifold for Cross-Modal Perception
Vincenzo Polizzi, David B. Lindell, Jonathan Kelly
Event cameras provide several unique advantages over standard frame-based sensors, including high temporal resolution, low latency, and robustness to extreme lighting. However, exi…
Efficient and Training-Free Single-Image Diffusion Models
Haojun Qiu, Kiriakos N. Kutulakos, David B. Lindell
We consider the problem of generating images whose internal structure -- defined by the distribution of patches across multiple scales -- matches that of a single reference image.…
SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers
Javad Rajabi, Kimia Shaban, Koorosh Roohi +2
Diffusion transformers (DiTs) have emerged as a dominant architecture for text-to-image generation, yet their performance drops when generating at resolutions beyond their training…
Velox: Learning Representations of 4D Geometry and Appearance
Anagh Malik, Dorian Chan, Xiaoming Zhao +3
We introduce a framework for learning latent representations of 4D objects which are descriptive, faithfully capturing object geometry and appearance; compressive, aiding in downst…
Addressing Image Authenticity When Cameras Use Generative AI
Umar Masud, Abhijith Punnappurath, Luxi Zhao +2
The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared online. Interestingly, images ca…
Skullptor: High Fidelity 3D Head Reconstruction in Seconds with Multi-View Normal Prediction
Noé Artru, Rukhshanda Hussain, Emeline Got +3
Reconstructing high-fidelity 3D head geometry from images is critical for a wide range of applications, yet existing methods face fundamental limitations. Traditional photogrammetr…
Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fields
Weihan Luo, Lily Goli, Sherwin Bahmani +3
Modeling the time-varying 3D appearance of plants during growth poses unique challenges: unlike most dynamic scenes, plants continuously generate new geometry as they expand, branc…
Dark3R: Learning Structure from Motion in the Dark
Andrew Y Guo, Anagh Malik, SaiKiran Tedla +7
We introduce Dark3R, a framework for structure from motion in the dark that operates directly on raw images with signal-to-noise ratios (SNRs) below dB -- a regime where conve…