1 citations · 1 across the 13 of their papers we have counts for
15 papers
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…
MVP4D: Multi-View Portrait Video Diffusion for Animatable 4D Avatars
Felix Taubner, Ruihang Zhang, Mathieu Tuli +2
Digital human avatars aim to simulate the dynamic appearance of humans in virtual environments, enabling immersive experiences across gaming, film, virtual reality, and more. Howev…
VibES: Induced Vibration for Persistent Event-Based Sensing
Vincenzo Polizzi, Stephen Yang, Quentin Clark +3
Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigid…
Generative Panoramic Image Stitching
Mathieu Tuli, Kaveh Kamali, David B. Lindell
We introduce the task of generative panoramic image stitching, which aims to synthesize seamless panoramas that are faithful to the content of multiple reference images containing…
CAP4D: Creating Animatable 4D Portrait Avatars with Morphable Multi-View Diffusion Models
Felix Taubner, Ruihang Zhang, Mathieu Tuli +1
Reconstructing photorealistic and dynamic portrait avatars from images is essential to many applications including advertising, visual effects, and virtual reality. Depending on th…
SCE-MAE: Selective Correspondence Enhancement with Masked Autoencoder for Self-Supervised Landmark Estimation
Kejia Yin, Varshanth R. Rao, Ruowei Jiang +3
Self-supervised landmark estimation is a challenging task that demands the formation of locally distinct feature representations to identify sparse facial landmarks in the absence…