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Found 20 papers, 14 papers with code
Automatic Controllable Colorization via Imagination
Unlike most previous end-to-end automatic colorization algorithms, our framework allows for iterative and localized modifications of the colorization results because we explicitly model the coloring samples.
Robust Depth Enhancement via Polarization Prompt Fusion Tuning
Existing depth sensors are imperfect and may provide inaccurate depth values in challenging scenarios, such as in the presence of transparent or reflective objects.
Neural Spline Fields for Burst Image Fusion and Layer Separation
Each photo in an image burst can be considered a sample of a complex 3D scene: the product of parallax, diffuse and specular materials, scene motion, and illuminant variation.
Thin On-Sensor Nanophotonic Array Cameras
The optical array is embedded on a metasurface that, at 700~nm height, is flat and sits on the sensor cover glass at 2. 5~mm focal distance from the sensor.
FateZero: Fusing Attentions for Zero-shot Text-based Video Editing
We also have a better zero-shot shape-aware editing ability based on the text-to-video model.
Blind Video Deflickering by Neural Filtering with a Flawed Atlas
Prior work usually requires specific guidance such as the flickering frequency, manual annotations, or extra consistent videos to remove the flicker.
FPR: False Positive Rectification for Weakly Supervised Semantic Segmentation
Without introducing any external supervision and human priors, the proposed FPR effectively suppresses wrong activations from the background objects.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
Randomized Quantization: A Generic Augmentation for Data Agnostic Self-supervised Learning
Self-supervised representation learning follows a paradigm of withholding some part of the data and tasking the network to predict it from the remaining part.
High-fidelity 3D GAN Inversion by Pseudo-multi-view Optimization
We present a high-fidelity 3D generative adversarial network (GAN) inversion framework that can synthesize photo-realistic novel views while preserving specific details of the input image.
Robust Reflection Removal with Flash-only Cues in the Wild
We propose a simple yet effective reflection-free cue for robust reflection removal from a pair of flash and ambient (no-flash) images.
Deep Video Prior for Video Consistency and Propagation
A progressive propagation strategy with pseudo labels is also proposed to enhance DVP's performance on video propagation.
Shape from Polarization for Complex Scenes in the Wild
We present a new data-driven approach with physics-based priors to scene-level normal estimation from a single polarization image.
Towards Photorealistic Colorization by Imagination
We present a novel approach to automatic image colorization by imitating the imagination process of human experts.
A Categorized Reflection Removal Dataset with Diverse Real-world Scenes
Due to the lack of a large-scale reflection removal dataset with diverse real-world scenes, many existing reflection removal methods are trained on synthetic data plus a small amount of real-world data, which makes it difficult to evaluate the strengths or weaknesses of different reflection removal methods thoroughly.
Neural Camera Simulators
To facilitate the learning of a simulator model, we collect a dataset of the 10, 000 raw images of 450 scenes with different exposure settings.
Robust Reflection Removal with Reflection-free Flash-only Cues
The flash-only image is equivalent to an image taken in a dark environment with only a flash on.
Blind Video Temporal Consistency via Deep Video Prior
Extensive quantitative and perceptual experiments show that our approach obtains superior performance than state-of-the-art methods on blind video temporal consistency.
Polarized Reflection Removal with Perfect Alignment in the Wild
We present a novel formulation to removing reflection from polarized images in the wild.
Video Depth Estimation by Fusing Flow-to-Depth Proposals
Our flow-to-depth layer is differentiable, and thus we can refine camera poses by maximizing the aggregated confidence in the camera pose refinement module.
Fully Automatic Video Colorization with Self-Regularization and Diversity
We present a fully automatic approach to video colorization with self-regularization and diversity.
