arXiv Computer Vision
TrackTok: Object-Centric Video Tokenization with Semantically Persistent Tokens
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
arXiv Computer Vision
Oct 21
TrajTok: Learning Trajectory Tokens enables better Video Understanding
TrajTok introduces an end‑to‑end video tokenizer that replaces traditional patchification with a lightweight, trajectory‑based tokenization process. It performs implicit clustering over space‑time pixels to generate object trajectories in a single forward pass, dynamically adjusting token granularity to semantic complexity while remaining independent of video duration. The resulting TrajViT2 model outperforms existing methods on classification and retrieval benchmarks, and TrajTok can also serve as a probing head (TrajAdapter) or alignment connector (TrajVLM) for vision‑language tasks, notably improving long‑video reasoning.
arXiv Computer Vision
Oct 2
SemanTok: Predictable Semantic Tokens for Efficient Autoregressive Video Generation
arXiv:2610.00686v1 Announce Type: new Abstract: Recent video-based world models pair the scalability of autoregressive (AR) prediction with the visual quality of diffusion models. The choice of scene...
arXiv AI
Jun 12
HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers
arXiv:2606. 13289v1 Announce Type: cross Abstract: Holistic visual tokenizers are fundamental to unified multimodal models (UMMs) as they map diverse visual inputs into a unified representation space.
Hugging Face Trending Papers
Aug 13
V-RAE: Rethinking Video Latent Spaces for Generation
Latent video generation relies on autoencoders to define a compact space in which generative models operate. Although video autoencoder architectures have evolved substantially, their latent spaces are still optimized primarily for pixel-level reconstruction and provide limited high-level semantic organization.
arXiv Computer Vision
Aug 26
Keep-or-Drop? Adaptive Tokenizer for Compact Video Representation
arXiv:2608.24293v1 Announce Type: new Abstract: Latent diffusion models have emerged as a dominant framework for high-fidelity image and video synthesis, operating in compact latent spaces with varia...
arXiv Computer Vision
Oct 15
KiToke: Distribution-Aware Token Compression for Video Large Language Models
arXiv:2604.03414v2 Announce Type: replace Abstract: Video Large Language Models (Video LLMs) achieve strong performance on video understanding tasks but suffer from high inference costs due to the la...