12 papers · 1 filter
Test-Time Noise Guided Adaptation for Realistic Autoregressive Video Generation
Dimitrios Karageorgiou, Symeon Papadopoulos, Ioannis Kompatsiaris +1
Autoregressive video diffusion models have enabled the generation of arbitrarily long videos by removing conditioning on future frames, thus greatly improving computational efficie…
Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
Antonios Tragoudaras, Chenyu Zhang, Daniil Cherniavskii +7
Recent advances in image and video generation raise hopes that these models possess world modeling capabilities-the ability to generate realistic, physically plausible videos. This…
Dual Guidance Semi-Supervised Action Detection
Ankit Singh, Efstratios Gavves, Cees G. M. Snoek +1
Semi-Supervised Learning (SSL) has shown tremendous potential to improve the predictive performance of deep learning models when annotations are hard to obtain. However, the applic…
MoSiC: Optimal-Transport Motion Trajectory for Dense Self-Supervised Learning
Mohammadreza Salehi, Shashanka Venkataramanan, Ioana Simion +3
Dense self-supervised learning has shown great promise for learning pixel- and patch-level representations, but extending it to videos remains challenging due to the complexity of…
Probabilistic Prototype Calibration of Vision-Language Models for Generalized Few-shot Semantic Segmentation
Jie Liu, Jiayi Shen, Pan Zhou +2
Generalized Few-Shot Semantic Segmentation (GFSS) aims to extend a segmentation model to novel classes with only a few annotated examples while maintaining performance on base clas…
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao +4
Interactive 3D segmentation has emerged as a promising solution for generating accurate object masks in complex 3D scenes by incorporating user-provided clicks. However, two critic…