Hugging Face Trending Papers
StreamErase: Towards Ultra-Fast Streaming Video Erasing
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arXiv Computer Vision
1d ago
StreamErase: Towards Ultra-Fast Streaming Video Erasing
arXiv:2610.20137v1 Announce Type: new Abstract: Current video object removal methods suffer from prohibitive latency (minutes per video) and non-causal processing that prevents real-time interaction....
arXiv Computer Vision
4d ago
High-Throughput Generative Video Super-Resolution on a Single Consumer GPU
The paper presents a zero‑shot framework for high‑throughput generative video super‑resolution (VSR) that operates on a single high‑end consumer GPU without retraining. It decouples spatial upscaling, handled by a time‑distilled one‑step diffusion backbone, from temporal stabilization, achieved with a lightweight pretrained flow‑based interpolator. A resolution‑aware hybrid attention scheme replaces high‑resolution global attention with neighborhood attention to improve scalability, achieving up to ~32 FPS at 720p and a 44% speedup at 4K on an NVIDIA RTX 4090, while maintaining competitive perceptual quality and temporal consistency on standard VSR benchmarks.
arXiv AI
Jun 2
StreamingVLM: Real-Time Understanding for Infinite Video Streams
arXiv:2510. 09608v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) could power real-time assistants and autonomous agents, but they face a critical challenge: understanding near-infinite video streams without escalating latency and memory usage.
arXiv Computer Vision
Sep 22
Streaming Video Editing with Easy Adaptation
arXiv:2609.24788v1 Announce Type: new Abstract: In this paper, we propose SVEET, a framework that requires merely training on a pretrained bidirectional video diffusion model but supports high-qualit...
arXiv AI
Jun 15
Fast Autoregressive Video Diffusion and World Models with Temporal Cache Compression and Sparse Attention
arXiv:2602. 01801v2 Announce Type: replace-cross Abstract: Autoregressive video diffusion models enable streaming generation, opening the door to long-form synthesis, video world models, and interactive neural game engines.
arXiv Computer Vision
Oct 1
TripleFlow: Training-Free Video Object Removal by Bridging Residual Editing and Native Generation
arXiv:2609.39157v1 Announce Type: new Abstract: Video object removal presents a uniquely difficult editing challenge. Because a removal prompt specifies only what to erase rather than what to generat...