Titlebook: Computer Vision – ECCV 2024; 18th European Confer Ale? Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

松軟

FEIGN

Schrittmacher und Defibrillatoren, output modalities, we propose to train a new PBR model that is tightly linked to a frozen RGB model using a novel cross-network communication paradigm. As the base RGB model is fully frozen, the proposed method retains its general performance and remains compatible with . IPAdapters for that base model.

畸形

學術討論會

circuit

Fortify

,SpatialFormer: Towards Generalizable Vision Transformers with?Explicit Spatial Understanding,etter generalization, we employ a decoder-only overall architecture and propose a bilateral cross-attention block for efficient interactions between context and spatial tokens. SpatialFormer learns transferable image representations with explicit scene understanding, where the output spatial tokens

URN

,OccWorld: Learning a?3D Occupancy World Model for?Autonomous Driving, obtain discrete scene tokens to describe the surrounding scenes. We then adopt a GPT-like spatial-temporal generative transformer to generate subsequent scene and ego tokens to decode the future occupancy and ego trajectory. Extensive experiments on nuScenes demonstrate the ability of OccWorld to e

aesthetic

,MyVLM: Personalizing VLMs for?User-Specific Queries,ng the language model to naturally integrate the target concept in its generated response. We apply our technique to BLIP-2 and LLaVA for personalized image captioning and further show its applicability for personalized visual question-answering. Our experiments demonstrate our ability to generalize

epicardium

,Power Variable Projection for?Initialization-Free Large-Scale Bundle Adjustment,s state-of-the-art results in terms of speed and accuracy. To our knowledge, this work is the first to address the scalability of BA without initialization opening new venues for initialization-free structure-from-motion.

UNT

,Co-synthesis of?Histopathology Nuclei Image-Label Pairs Using a?Context-Conditioned Joint Diffusionlated text prompts to incorporate spatial and structural context information into the generation targets. Moreover, we enhance the granularity of our synthesized semantic labels by generating instance-wise nuclei labels using distance maps synthesized concurrently in conjunction with the images and