PicoEyes delivers a unified end-to-end model for full 3D gaze estimation including eye parameters, axes, segmentation and depth from monocular or binocular near-eye images, supported by a new large-scale multi-view dataset.
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Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612
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MU-GeNeRF combines source-view and target-view uncertainties via a heteroscedastic loss to enable distractor-aware generalizable NeRF reconstruction that matches scene-specific methods.
DreamStereo uses GAPW, PBDP, and SASI to enable real-time stereo video inpainting at 25 FPS for HD videos by reducing over 70% redundant computation while maintaining quality.
MultiAnimate adds Identifier Assigner and Identifier Adapter modules to diffusion video models so they can handle multiple characters without identity mix-ups, generalizing from two-character training data to more characters.
MagicBokeh uses a single diffusion model with alternative training, focus-aware masked attention, and degradation-aware depth estimation to produce photorealistic bokeh on low-res zoomed images.
TM-BSN introduces triangular-masked convolutions that align blind spots with diamond-shaped noise correlations from camera demosaicing, enabling stronger self-supervised denoising at full resolution without downsampling.
ComMark embeds covert watermarks in models using frequency-domain compressed samples and simulated attacks, claiming state-of-the-art covertness and robustness across image, speech, text, and video tasks.
Splatent recovers fine details for latent-space 3D Gaussian Splatting by applying multi-view attention in 2D rather than reconstructing in 3D space.
CylinderDepth uses cylindrical spatial attention with non-learned weights to enforce cross-view consistency in self-supervised surround depth estimation.
citing papers explorer
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PicoEyes: Unified Gaze Estimation Framework for Mixed Reality with a Large-Scale Multi-View Dataset
PicoEyes delivers a unified end-to-end model for full 3D gaze estimation including eye parameters, axes, segmentation and depth from monocular or binocular near-eye images, supported by a new large-scale multi-view dataset.
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MU-GeNeRF: Multi-view Uncertainty-guided Generalizable Neural Radiance Fields for Distractor-aware Scene
MU-GeNeRF combines source-view and target-view uncertainties via a heteroscedastic loss to enable distractor-aware generalizable NeRF reconstruction that matches scene-specific methods.
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DreamStereo: Towards Real-Time Stereo Inpainting for HD Videos
DreamStereo uses GAPW, PBDP, and SASI to enable real-time stereo video inpainting at 25 FPS for HD videos by reducing over 70% redundant computation while maintaining quality.
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MultiAnimate: Pose-Guided Image Animation Made Extensible
MultiAnimate adds Identifier Assigner and Identifier Adapter modules to diffusion video models so they can handle multiple characters without identity mix-ups, generalizing from two-character training data to more characters.
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Towards Photorealistic and Efficient Bokeh Rendering via Diffusion Framework
MagicBokeh uses a single diffusion model with alternative training, focus-aware masked attention, and degradation-aware depth estimation to produce photorealistic bokeh on low-res zoomed images.
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TM-BSN: Triangular-Masked Blind-Spot Network for Real-World Self-Supervised Image Denoising
TM-BSN introduces triangular-masked convolutions that align blind spots with diamond-shaped noise correlations from camera demosaicing, enabling stronger self-supervised denoising at full resolution without downsampling.
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ComMark: Covert and Robust Black-Box Model Watermarking with Compressed Samples
ComMark embeds covert watermarks in models using frequency-domain compressed samples and simulated attacks, claiming state-of-the-art covertness and robustness across image, speech, text, and video tasks.
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Splatent: Splatting Diffusion Latents for Novel View Synthesis
Splatent recovers fine details for latent-space 3D Gaussian Splatting by applying multi-view attention in 2D rather than reconstructing in 3D space.
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CylinderDepth: Cylindrical Spatial Attention for Multi-View Consistent Self-Supervised Surround Depth Estimation
CylinderDepth uses cylindrical spatial attention with non-learned weights to enforce cross-view consistency in self-supervised surround depth estimation.
- TWINGS: Thin Plate Splines Warp-aligned Initialization for Sparse-View Gaussian Splatting