Partially Relevant Video Retrieval (PRVR) seeks to retrieve untrim-med videos containing a moment that matches a text query, without temporal annotations. The relevant moment may last only seconds within a video spanning several minutes, creating an extremely low signal-to-noise ratio that makes PRVR more challenging t...
Zhen Liu, Le-Tian Li, Jinpeng Wang et al.· 0 citations
This work designs Progressive State Sequence Generation (PSSG) to construct complementary spatial-frequency target states (defining what to recover), and State Transition Evolution (STE) to adapt lightweight transition operators via a restoration-oriented TTT inner loop (determining how the features should evolve).
Kai-Han Zheng, Jun Li, Hang Guo et al.· 0 citations
Long-document understanding requires locating sparse and heterogeneous evidence across hundreds of pages, yet existing systems remain limited by static retrieval and fragile cross-round memory. Mainstream single-round methods commit to a fixed top-$k$ page set at the outset and struggle to recover from early retrieval...
Hanshu Yao, Janfeng Zhong, Niu Lian et al.· 0 citations
LAWM-3D is proposed, which introduces three tightly coupled key designs: a multi-view invariant unified action tokenization scheme for learning 3D-aware latent actions, a geometric alignment constraint that anchors intermediate encoder features to a pretrained 3D foundation model, and a non-injective RGB-D joint recons...
Jia-Rui Yang, Jiale Zhange, Jiawei Li et al.· 1 citation
A Video Compression framework built upon a foundational flow model that enables the compressor to harness generative video flow priors effectively, which reduces bit consumption by 58\% and achieves one-step decoding and reconstructions with high perceptual fidelity.
Yichong Xia, Qin-Hong Wu, Bin Chen et al.· 1 citation· ⚡1
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