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

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書(shū)目名稱(chēng)Computer Vision – ECCV 2024影響因子(影響力)




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書(shū)目名稱(chēng)Computer Vision – ECCV 2024讀者反饋




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,Diagnosing and?Re-learning for?Balanced Multimodal Learning,ach modality is firstly estimated based on the separability of its uni-modal representation space, and then used to softly re-initialize the corresponding uni-modal encoder. In this way, the over-emphasizing of scarcely informative modalities is avoided. In addition, encoders of worse-learnt modalit

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,SpaRP: Fast 3D Object Reconstruction and?Pose Estimation from?Sparse Views, the input sparse views. These predictions are then leveraged to accomplish 3D reconstruction and pose estimation, and the reconstructed 3D model can be used to further refine the camera poses of input views. Through extensive experiments on three datasets, we demonstrate that our method not only si

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LITA: Language Instructed Temporal-Localization Assistant,g video datasets with timestamps, we propose a new task, Reasoning Temporal Localization (RTL), along with the dataset, ActivityNet-RTL, for learning and evaluating this task. Reasoning temporal localization requires both the reasoning and temporal localization of Video LLMs. LITA demonstrates stron