Hugging Face Trending Papers
A Dual-Transformer for Multi-Camera View Recommendation
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arXiv Computer Vision
2d ago
A Dual-Transformer for Multi-Camera View Recommendation
The paper introduces a Dual-Transformer architecture with Cross-Attention for multi-camera view recommendation, achieving a 56.60% Precision@0.5 on the TVMCE dataset, surpassing the previous best of 37.16%. The model separates temporal encoding of past frames from candidate view querying, and an ablation study shows the SwinV2 backbone yields 69.65% Precision@0.5. Fine‑tuning with as little as 20% of a target video improves precision, suggesting efficient personalization for specific editing styles.
arXiv Machine Learning
2d ago
Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing
arXiv:2601.16296v3 Announce Type: replace-cross Abstract: Video-to-video diffusion models achieve impressive single-turn editing performance, but practical editing workflows are inherently iterative....
arXiv AI
Aug 6
ZoomV: Temporal Zoom-in for Efficient Long Video Understanding
arXiv:2504. 01407v3 Announce Type: replace-cross Abstract: Long video understanding poses a fundamental challenge for large video-language models (LVLMs) due to the overwhelming number of frames and the risk of losing essential context through naive downsampling.
Hugging Face Trending Papers
Jun 29
Goku: A Million-Scale Universal Dataset and Benchmark for Instruction-Based Video Editing
Existing instruction-based video editing datasets commonly focus on single-task appearance editing, failing to meet the complex creative demands of real-world scenarios. To bridge this gap, we present Goku, a large-scale dataset featuring 2 million high-quality, instruction-aligned video editing pairs, which is the first to extend task boundaries from basic appearance editing to multi-task and structural manipulations(e.
arXiv AI
Jun 9
CoVEBench: Can Video Editing Models Handle Complex Instructions?
arXiv:2606. 08415v1 Announce Type: cross Abstract: While recent text-guided video editing models excel at elementary tasks (e.
Hugging Face Trending Papers
Aug 3
MIEScore: Human-Aligned Evaluation for Multi-Source Image Editing
Recent advances in unified multimodal models have significantly improved text-guided image editing abilities. In particular, models such as Nano-Banana-Pro and GPT-Image-2 demonstrate emerging capabilities in multi-source image editing (MIE), including tasks such as object synthesis, person-background composition, and cross-image style fusion.