Jamp, R.M.[Ruei Ming]
* 1991: Method and apparatus for extracting information from forms
Includes: Jamp, R.M.[Ruei Ming] Jamp, R.M.[Ruei-Ming]
Jampala, R.
* 2017: Automatic delineation of macular regions based on a locally defined contrast function
Jampana, P.[Phanindra]
* 2012: image differencing method for interface level detection in separation cells, An
* 2016: Composition of Binary Compressed Sensing Matrices
* 2021: Construction of Binary Matrices as a Union of Orthogonal Blocks via Generalized Euler Squares
* 2021: Nullspace Property for Optimality of Minimum Frame Angle Under Invertible Linear Operators
Includes: Jampana, P.[Phanindra] Jampana, P.
Jampana, P.V.
* 2015: Optimization of Low-Dose Tomography via Binary Sensing Matrices
Jampani, V.[Varun]
* 2015: Efficient Facade Segmentation Using Auto-context
* 2015: informed sampler: A discriminative approach to Bayesian inference in generative computer vision models, The
* 2016: Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks
* 2016: Optical Flow with Semantic Segmentation and Localized Layers
* 2016: Superpixel Convolutional Networks Using Bilateral Inceptions
* 2017: Semantic Video CNNs Through Representation Warping
* 2017: Video Propagation Networks
* 2018: Efficient 2D and 3D Facade Segmentation Using Auto-Context
* 2018: Learning Superpixels with Segmentation-Aware Affinity Loss
* 2018: On the Integration of Optical Flow and Action Recognition
* 2018: SPLATNet: Sparse Lattice Networks for Point Cloud Processing
* 2018: Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation
* 2018: Superpixel Sampling Networks
* 2018: Switchable Temporal Propagation Network
* 2018: Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization
* 2019: Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation
* 2019: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation
* 2019: Learning Propagation for Arbitrarily-Structured Data
* 2019: Pixel-Adaptive Convolutional Neural Networks
* 2019: SCOPS: Self-Supervised Co-Part Segmentation
* 2019: SENSE: A Shared Encoder Network for Scene-Flow Estimation
* 2020: Appearance Consensus Driven Self-supervised Human Mesh Recovery
* 2020: DeepGMR: Learning Latent Gaussian Mixture Models for Registration
* 2020: From Image Collections to Point Clouds With Self-Supervised Shape and Pose Networks
* 2020: Intrinsic Autoencoders for Joint Deferred Neural Rendering and Intrinsic Image Decomposition
* 2020: Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesis
* 2020: Self-supervised Single-view 3d Reconstruction via Semantic Consistency
* 2020: Self-Supervised Viewpoint Learning From Image Collections
* 2020: Two-Shot Spatially-Varying BRDF and Shape Estimation
* 2021: Adaptive Prototype Learning and Allocation for Few-Shot Segmentation
* 2021: AutoFlow: Learning a Better Training Set for Optical Flow
* 2021: Decoupled Dynamic Filter Networks
* 2021: Discovering 3D Parts from Image Collections
* 2021: Generalize then Adapt: Source-Free Domain Adaptive Semantic Segmentation
* 2021: Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image
* 2021: NeRD: Neural Reflectance Decomposition from Image Collections
* 2021: SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting
* 2022: Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
* 2022: Hierarchical Semantic Regularization of Latent Spaces in StyleGANs
* 2022: Improving GANs for Long-Tailed Data Through Group Spectral Regularization
* 2022: LEAD: Self-Supervised Landmark Estimation by Aligning Distributions of Feature Similarity
* 2022: Learning ABCs: Approximate Bijective Correspondence for isolating factors of variation with weak supervision
* 2022: Multi-Frame Video Prediction with Learnable Motion Encodings
* 2022: Planes vs. Chairs: Category-Guided 3D Shape Learning Without any 3D Cues
* 2022: SOMSI: Spherical Novel View Synthesis with Soft Occlusion Multi-Sphere Images
* 2022: Uncertainty-Aware Adaptation for Self-Supervised 3D Human Pose Estimation
* 2023: ASIC: Aligning Sparse in-the-wild Image Collections
* 2023: DreamBooth3D: Subject-Driven Text-to-3D Generation
* 2023: DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
* 2023: Hi-LASSIE: High-Fidelity Articulated Shape and Skeleton Discovery from Sparse Image Ensemble
* 2023: LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding
* 2023: LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs
* 2023: MetaCLUE: Towards Comprehensive Visual Metaphors Research
* 2023: NoisyTwins: Class-Consistent and Diverse Image Generation Through StyleGANs
* 2023: ShapeClipper: Scalable 3D Shape Learning from Single-View Images via Geometric and CLIP-Based Consistency
Includes: Jampani, V.[Varun] Jampani, V.
55 for Jampani, V.
Jampel, H.
* 2009: Image Based Auto-Focusing Algorithm for Digital Fundus Photography, An
Jampour, M.[Mahdi]
* 2009: Compressing of Fingerprint Images by Means of Fractals Feature
* 2015: Pairwise linear regression: An efficient and fast multi-view facial expression recognition
* 2017: Face inpainting based on high-level facial attributes
* 2017: Pose-specific non-linear mappings in feature space towards multiview facial expression recognition
* 2018: Mapping Forests: A Comprehensive Approach for Nonlinear Mapping Problems
* 2019: Chaos game theory and its application for offline signature identification
* 2021: CapsNet regularization and its conjugation with ResNet for signature identification
* 2021: Facial Expression Recognition using Multi-Feature Concatenation of Local Face Components and Hierarchical SVM
* 2022: IAUFD: A 100k images dataset for automatic football image/video analysis
* 2022: Multiview Facial Expression Recognition, A Survey
10 for Jampour, M.