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

JOT

水槽

https://doi.org/10.1007/978-3-658-32307-3and quantitatively on the well-known MERL dataset of 100 isotropic materials. Our approach accurately 1) estimates the BRDFs of unseen materials even for an extremely sparse sampling, 2) compresses the measured BRDFs into very small embeddings, e.g., 7D.

ANIM

哪有黃油

Conference proceedings 2025uter Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024...The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforceme

Explosive

0302-9743 ce on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024...The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; r

信徒

,WTS: A Pedestrian-Centric Traffic Video Dataset for?Fine-Grained Spatial-Temporal Understanding,ng WTS, we establish a benchmark for dense video-to-text tasks, exploring state-of-the-art Vision-Language Models with an instance-aware VideoLLM method as a baseline. WTS aims to advance fine-grained video event understanding, enhancing traffic safety and autonomous driving development. Dataset pag

水獺

Spiking Wavelet Transformer,ing, 2) convolution-based learner for spatial feature extraction, and 3) spiking pointwise convolution for cross-channel information aggregation - with negative spike dynamics incorporated in 1) to enhance frequency representation. The FATM enables the SWformer to outperform vanilla Spiking Transfor

malapropism

,WAVE: Warping DDIM Inversion Features for?Zero-Shot Text-to-Video Editing,rames randomly in each timestep and use optical flow extracted from the source video to propagate the latent features of the first keyframe to subsequent keyframes. Moreover, we develop a comprehensive zero-shot framework that adapts to this strategy in both the inversion and denoising processes, th

使乳化

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