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Found 12 papers, 3 papers with code
Spike-NeRF: Neural Radiance Field Based On Spike Camera
As a neuromorphic sensor with high temporal resolution, spike cameras offer notable advantages over traditional cameras in high-speed vision applications such as high-speed optical estimation, depth estimation, and object tracking.
Learning to Robustly Reconstruct Low-light Dynamic Scenes from Spike Streams
In this paper, we propose a bidirectional recurrent-based reconstruction framework, including a Light-Robust Representation (LR-Rep) and a fusion module, to better handle such extreme conditions.
VOODOO 3D: Volumetric Portrait Disentanglement for One-Shot 3D Head Reenactment
We present a 3D-aware one-shot head reenactment method based on a fully volumetric neural disentanglement framework for source appearance and driver expressions.
Spike Stream Denoising via Spike Camera Simulation
Based on our noise model, the first benchmark for spike stream denoising is proposed which includes clear (noisy) spike stream.
1000 FPS HDR Video With a Spike-RGB Hybrid Camera
Capturing high frame rate and high dynamic range (HFR&HDR) color videos in high-speed scenes with conventional frame-based cameras is very challenging.
Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion
We present a framework for modeling interactional communication in dyadic conversations: given multimodal inputs of a speaker, we autoregressively output multiple possibilities of corresponding listener motion.
A Robust Visual Sampling Model Inspired by Receptive Field
More importantly, due to mimicking receptive field mechanism to collect regional information, RVSM can filter high intensity noise effectively and improves the problem that Spike camera is sensitive to noise largely.
Watch Those Words: Video Falsification Detection Using Word-Conditioned Facial Motion
In today's era of digital misinformation, we are increasingly faced with new threats posed by video falsification techniques.
Optical Flow Estimation for Spiking Camera
Further, for training SCFlow, we synthesize two sets of optical flow data for the spiking camera, SPIkingly Flying Things and Photo-realistic High-speed Motion, denoted as SPIFT and PHM respectively, corresponding to random high-speed and well-designed scenes.
Normalized Avatar Synthesis Using StyleGAN and Perceptual Refinement
Cutting-edge 3D face reconstruction methods use non-linear morphable face models combined with GAN-based decoders to capture the likeness and details of a person but fail to produce neutral head models with unshaded albedo textures which is critical for creating relightable and animation-friendly avatars for integration in virtual environments.
Real-Time Hair Rendering using Sequential Adversarial Networks
To handle the diversity of hairstyles and its appearance complexity, we disentangle hair structure, color, and illumination properties using a sequential GAN architecture and a semi-supervised training approach.
Photorealistic Facial Texture Inference Using Deep Neural Networks
We present a data-driven inference method that can synthesize a photorealistic texture map of a complete 3D face model given a partial 2D view of a person in the wild.
