arXiv AI
Jun 10
Pose-ICL: 3D-Aware In-Context Learning for Pose-Controllable Subject Customization
arXiv:2606. 10902v1 Announce Type: cross Abstract: Subject Customization is a foundational task in modern image generation.
Direct 3D-Aware Object Insertion via Decomposed Visual Proxies
arXiv:2606. 06601v1 Announce Type: cross Abstract: Object insertion aims to seamlessly composite a reference object into a specified region of a background image.
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arXiv AI
Jul 2
Interact3D: Compositional 3D Generation of Interactive Objects
arXiv:2603. 16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets.
arXiv AI
Jun 30
InsertAnywhere: Geometrically Grounded and Optics-Aware Video Object Insertion
arXiv:2512. 17504v2 Announce Type: replace-cross Abstract: Recent advances in diffusion models have enabled impressive video editing capabilities, yet production-grade Video Object Insertion (VOI) remains challenging due to inadequate 4D scene understanding and a lack of proper optical interactions, such as shadows and reflections.
arXiv AI
Aug 7
UniVVT: A Unified End-to-End Framework for High-Fidelity Video Virtual Try-on
arXiv:2608. 05745v1 Announce Type: cross Abstract: Video Virtual Try-On (VVT) synthesizes a video of a person wearing a target garment while preserving identity, motion, and scene dynamics.
arXiv AI
Jun 29
CoIn: Comprehensive 2D-3D Inpainting with Gaussian Splatting Guidance
arXiv:2606. 27584v1 Announce Type: cross Abstract: 3D scene inpainting is essential for reconstructing areas corrupted by occlusions or limited viewpoints.
arXiv Machine Learning
Jun 30
R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow
arXiv:2605. 13838v3 Announce Type: replace-cross Abstract: Video-guided 3D animation holds immense potential for content creation, offering intuitive and precise control over dynamic assets.
arXiv AI
Jun 18
VidCRAFT3: Camera, Object, and Lighting Control for Image-to-Video Generation
arXiv:2502. 07531v5 Announce Type: replace-cross Abstract: Controllable image-to-video (I2V) generation transforms a reference image into a coherent video guided by user-specified control signals.
arXiv AI
Aug 11
Controllable Video Object Insertion via Multi-View Priors
arXiv:2604. 14556v2 Announce Type: replace-cross Abstract: Video object insertion places a user-specified object in an existing dynamic scene.
Hugging Face Trending Papers
Jul 27
CameraAnything: Refilming Videos with Arbitrary Camera Control
We introduce CameraAnything, the first unified framework for camera controlled video editing that enables joint control of both intrinsic and extrinsic camera parameters. Existing approaches either rely on expensive 3D reconstruction to achieve full camera functionality or restrict editing to extrinsic parameter manipulation.
arXiv AI
Jun 8
Beyond Skeletons: Learning Animation Directly from Driving Videos with Same2X Training Strategy
arXiv:2606. 06903v1 Announce Type: cross Abstract: Human image animation aims to generate a video from a static reference image, guided by pose information extracted from a driving video.
arXiv AI
Jun 4
SAM 3D: 3Dfy Anything in Images
arXiv:2511. 16624v2 Announce Type: replace-cross Abstract: We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image.
arXiv Machine Learning
Jun 8
TrioPose: Native Triple-Stream Diffusion Transformers for Pose-Guided Text-to-Image Generation
arXiv:2606. 07053v1 Announce Type: cross Abstract: Pose-guided text-to-image generation often suffers from limb distortions and feature crosstalk in complex multi-person scenarios.