XAttnRes introduces cross-stage attention residuals that maintain a global feature history and selectively aggregate prior representations, improving medical image segmentation and performing on par with baselines even without skip connections.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.CV 3years
2026 3verdicts
UNVERDICTED 3roles
method 1polarities
use method 1representative citing papers
Hybrid Domain Knowledge Fusion distills expertise from specialized models across synthetic, OLAT, and real datasets into a lightweight student model for state-of-the-art portrait relighting with 6x-240x faster inference.
UNICA unifies motion planning, rigging, physical simulation, and rendering into a single skeleton-free neural framework that produces next-frame 3D avatar geometry from action inputs and renders it with Gaussian splatting.
citing papers explorer
-
XAttnRes: Cross-Stage Attention Residuals for Medical Image Segmentation
XAttnRes introduces cross-stage attention residuals that maintain a global feature history and selectively aggregate prior representations, improving medical image segmentation and performing on par with baselines even without skip connections.
-
Toward Real-World Adoption of Portrait Relighting via Hybrid Domain Knowledge Fusion
Hybrid Domain Knowledge Fusion distills expertise from specialized models across synthetic, OLAT, and real datasets into a lightweight student model for state-of-the-art portrait relighting with 6x-240x faster inference.
-
UNICA: A Unified Neural Framework for Controllable 3D Avatars
UNICA unifies motion planning, rigging, physical simulation, and rendering into a single skeleton-free neural framework that produces next-frame 3D avatar geometry from action inputs and renders it with Gaussian splatting.