All papers

The paper proposes a deep unfolding network integrating manifold optimization for unsupervised feature selection in image processing.

The paper proposes a deep unfolding network integrating manifold optimization for unsupervised feature selection in image processing.

The paper proposes a depth-conditioned diffusion transformer architecture to suppress overlapping bone structures in chest X-ray images.

The paper proposes a depth-conditioned diffusion transformer architecture to suppress overlapping bone structures in chest X-ray images.

The paper introduces an embedding model that jointly encodes vision, language, and action to retrieve relevant historical trajectories for robot learning.

The paper introduces a generative pipeline to reconstruct multi-room 3D environments from sparse panorama images using geometric optimization.

The paper introduces a synthetic world generator and benchmark for evaluating 3D hyperspectral material unmixing within novel view rendering.

The paper introduces a rank-calibration framework to improve proposal localization quality for temporal action detection in long untrimmed videos.

The paper proposes a loss function that reduces spatial neighborhood discrepancies in space-filling curve representations for 3D point cloud segmentation.

The paper proposes a loss function that reduces spatial neighborhood discrepancies in space-filling curve representations for 3D point cloud segmentation.

The paper proposes an optimization method for 3D Gaussian Splatting that improves rate-distortion performance when compressing scenes with image codecs.

The paper proposes an optimization method for 3D Gaussian Splatting that improves rate-distortion performance when compressing scenes with image codecs.

The paper presents a domain-generalization method to detect industrial board defects reliably across varied production environments and lighting conditions.

The paper introduces TEXTVERIFIER, a verification framework using character structural sequences to detect fine rendering defects in generated Chinese text.

The paper introduces FLARE, a visual speech framework combining cross-modal distillation from audio features with dual-stream face and lip modeling.

The paper proposes a step-wise alignment method to suppress harmful content in text-to-image models while maintaining generation semantics.

Uses factorial interventions to locate failure points in multi-image vision-language reasoning pipelines.

Introduces a benchmark dataset and baseline architecture for reconstructing standalone 3D garments from single images.

Adapts both field of view and fixation counts per image to optimize computation in active visual recognition.

Adapts both field of view and fixation counts per image to optimize computation in active visual recognition.

Proves theoretically that self-conditioning enables genuine multi-step reasoning in flow matching where standard samplers fail.

Proves theoretically that self-conditioning enables genuine multi-step reasoning in flow matching where standard samplers fail.

Proves theoretically that self-conditioning enables genuine multi-step reasoning in flow matching where standard samplers fail.

Proves theoretically that self-conditioning enables genuine multi-step reasoning in flow matching where standard samplers fail.

Delineates Arctic coastal polynyas from satellite sea ice concentration data using hierarchical partitioning and region growing.

Delineates Arctic coastal polynyas from satellite sea ice concentration data using hierarchical partitioning and region growing.

Transfers hyperspectral tokens into frozen vision-language-action models via learned continuous residuals without retraining.

Equips frozen 3D geometry foundation models with an associative external memory to revise past predictions across long horizons.

Equips frozen 3D geometry foundation models with an associative external memory to revise past predictions across long horizons.

Reconstructs mixed-reflectance 3D surfaces by integrating microfacet normal consistency into neural implicit distance fields.

Reconstructs mixed-reflectance 3D surfaces by integrating microfacet normal consistency into neural implicit distance fields.

Adds content-addressable associative memory to latent world models to prevent collapse and improve long-horizon planning.

Adds content-addressable associative memory to latent world models to prevent collapse and improve long-horizon planning.

Adds content-addressable associative memory to latent world models to prevent collapse and improve long-horizon planning.

Adds content-addressable associative memory to latent world models to prevent collapse and improve long-horizon planning.

Couples a persistent symbolic world engine with an egocentric generative model for continuous interactive audiovisual simulation.

Identifies scale mismatches as the cause of trajectory drift in monocular human recovery under rapid camera movement.

Identifies scale mismatches as the cause of trajectory drift in monocular human recovery under rapid camera movement.

Presents a trust-region optimization method using dual quaternions to estimate 3D object pose from 2D correspondences.

Presents a trust-region optimization method using dual quaternions to estimate 3D object pose from 2D correspondences.

Incorporates hyperspectral imaging descriptors into 3D Gaussian Splatting loop closure to prevent visual aliasing in planetary SLAM.

Incorporates hyperspectral imaging descriptors into 3D Gaussian Splatting loop closure to prevent visual aliasing in planetary SLAM.

Extracts generative image priors directly from the loss-gradient geometry of pretrained discriminative models without retraining.

Extracts generative image priors directly from the loss-gradient geometry of pretrained discriminative models without retraining.

Extracts generative image priors directly from the loss-gradient geometry of pretrained discriminative models without retraining.

Extracts generative image priors directly from the loss-gradient geometry of pretrained discriminative models without retraining.

Extracts generative image priors directly from the loss-gradient geometry of pretrained discriminative models without retraining.

Audits physics-guided underwater image restoration models, showing image-formation priors provide minimal benefit under full training data.

Audits physics-guided underwater image restoration models, showing image-formation priors provide minimal benefit under full training data.

Generates quad-only 3D meshes autoregressively using a singularity-aware tokenization scheme that preserves strict topology.

Generates quad-only 3D meshes autoregressively using a singularity-aware tokenization scheme that preserves strict topology.

Formulates computational compressive imaging reconstruction as an Ising model solved via simulated annealing.

Formulates computational compressive imaging reconstruction as an Ising model solved via simulated annealing.

Introduces a benchmark dataset to localize impact moments in drone first-person-view crash videos for post-flight analysis.

Introduces a benchmark dataset to localize impact moments in drone first-person-view crash videos for post-flight analysis.

Improves active domain adaptation for difficult classes using region-based positive manifold coverage and uncertainty scoring.

Improves active domain adaptation for difficult classes using region-based positive manifold coverage and uncertainty scoring.

Introduces a diagnostic question-answering benchmark to evaluate whether text-to-video models follow real-world physical laws.

Evaluates four world-model integration paradigms to identify what improves vision-language-action policies in robotic tasks.

Combines 3D Gaussian Splatting with ray-traced occlusion estimation to enable relighting and material decomposition.