arXiv AI
Jul 7
Motion Attribution for Video Generation
arXiv:2601. 08828v2 Announce Type: replace-cross Abstract: Despite the rapid progress of video generation models, the role of data in influencing motion is poorly understood.
Your Data Manifold is Secretly a Reward Model: Shell-LCC for Text-to-Video Generation
arXiv:2606. 30248v1 Announce Type: cross Abstract: Recent text-to-video (T2V) diffusion models rely heavily on auxiliary reward signals (e.
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arXiv Machine Learning
Jun 9
MilliVid: Hierarchical Latents for Long-Range Consistency in Video Generation
arXiv:2606. 09056v1 Announce Type: cross Abstract: Video generative models have become increasingly powerful, but long-range consistency remains challenging to achieve because even a few dozen frames require impractically long transformer sequence lengths.
arXiv AI
Jun 9
VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation
arXiv:2601. 23286v4 Announce Type: replace-cross Abstract: While recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, often resulting in object deformation or spatial drift.
arXiv AI
Jun 30
MotionAtlas: Detailed Region Captioning for Motion-Centric Videos
arXiv:2606. 29531v1 Announce Type: cross Abstract: We propose MotionAtlas, a system for detailed captioning of motion-centric videos, comprising (1) a dedicated human-annotated benchmark, (2) a scalable, high-quality pipeline to construct training samples, and (3) a family of powerful Video-MLLMs.
Hugging Face Trending Papers
Jul 2
NeoMap: Training-free Novel-View Synthesis from Single Images and Videos
We study the challenging problem of novel view video synthesis from single images or monocular videos. Existing methods, which operate under the assumption that pre-trained video models lack native novel view synthesis capability and enforce view alignment via camera conditioning, task-specific fine-tuning, or stepwise hard denoising guidance, often suffer from artifacts and compromised global scene consistency.
arXiv Machine Learning
Jul 9
Gen4U: Unifying Video Generation and Understanding via Diffusion
arXiv:2607. 06856v1 Announce Type: cross Abstract: Prior work suggests that diffusion representations capture low-level geometry but struggle with high-level semantics.
arXiv AI
Jul 3
NeoMap: Training-free Novel-View Synthesis from Single Images and Videos
arXiv:2607. 01962v1 Announce Type: cross Abstract: We study the challenging problem of novel view video synthesis from single images or monocular videos.
Hugging Face Trending Papers
Aug 10
Illusion or Integrity? Geometrical Consistency Metric for AIGC Video Quality Evaluation
Recently, AI-driven video generation has attracted considerable attention. This surge increases the demand for reliable video quality assessment (VQA) metrics to evaluate AI-generated content (AIGC) videos and guide model optimization.
arXiv AI
Aug 6
CARVE: Cross-Slice Anisotropic Reallocation of Visual Evidence for Efficient 3D Medical Volume Understanding
arXiv:2608. 04515v1 Announce Type: cross Abstract: Slice-based MLLMs leverage mature 2D encoders by representing 3D volumes as sequences of 2D slices.
arXiv AI
Aug 11
Illusion or Integrity? Geometrical Consistency Metric for AIGC Video Quality Evaluation
arXiv:2608. 09594v1 Announce Type: cross Abstract: Recently, AI-driven video generation has attracted considerable attention.
arXiv AI
Jun 24
When Language Overwrites Vision: Over-Alignment and Geometric Debiasing in Vision-Language Models
arXiv:2605. 08245v4 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) increasingly power high-stakes applications, from medical imaging to autonomous systems, yet they routinely hallucinate, confidently describing content not present in the input.
arXiv Machine Learning
Jul 23
WorldPack: Dynamic Frame Compression for Long-context Video World Modeling
arXiv:2512. 02473v2 Announce Type: replace-cross Abstract: Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on past observations and navigation actions.