Publications

iDisc: Internal Discretization for Monocular Depth Estimation

iDisc: Internal Discretization for Monocular Depth Estimation

CVPR 2023 We propose a monocular depth estimation method which represents internally the scene as a finite set of concepts via a continuous-discrete-continuous bottleneck

Mask-Free Video Instance Segmentation

Mask-Free Video Instance Segmentation

CVPR 2023 We remove video and image mask annptation necessity for training highly accurate VIS models.

Uncertainty-Driven Dense Two-View Structure from Motion

Uncertainty-Driven Dense Two-View Structure from Motion

RA-L 2023 We introduce an uncertainty-driven Dense Two-View SfM pipeline.

TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction

TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction

ICRA 2023 We present TrafficBots, a multi-agent policy built upon motion prediction and end-to-end driving.

Dense Prediction with Attentive Feature Aggregation

Dense Prediction with Attentive Feature Aggregation

WACV 2023 We propose Attentive Feature Aggregation (AFA) to exploit both spatial and channel information for semantic segmentation and boundary detection.

Spatio-Temporal Action Detection Under Large Motion

Spatio-Temporal Action Detection Under Large Motion

WACV 2023 We propose to enhance actor feature representation under large motion by tracking actors and performing temporal feature aggregation along the respective tracks.

Composite Learning for Robust and Effective Dense Predictions

Composite Learning for Robust and Effective Dense Predictions

WACV 2023 We find that jointly training a dense prediction task with a self-supervised task can consistently improve the performance of the target task.

CC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion

CC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion

CoRL 2022 We propose a method for panoramic 3D object tracking, called CC-3DT, that associates and models object trajectories both temporally and across views.

Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields

Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields

RA-L 2022 This paper introduces a ray-based volumetric uncertainty estimator, which computes the entropy of the weight distribution of the color samples along each ray of the object’s implicit neural representation.

Tracking Every Thing in the Wild

Tracking Every Thing in the Wild

ECCV 2022 We introduce a new metric, Track Every Thing Accuracy (TETA), and a Track Every Thing tracker (TETer), which performs association using Class Exemplar Matching (CEM).

Video Mask Transfiner for High-Quality Video Instance Segmentation

Video Mask Transfiner for High-Quality Video Instance Segmentation

ECCV 2022 We propose Video Mask Transfiner (VMT) method, capable of leveraging fine-grained high-resolution features thanks to a highly efficient video transformer structure.

SAGA: Stochastic Whole-Body Grasping with Contact

SAGA: Stochastic Whole-Body Grasping with Contact

ECCV 2022 We propose SAGA (StochAstic whole-body Grasping with contAct).

Learning Online Multi-Sensor Depth Fusion

Learning Online Multi-Sensor Depth Fusion

ECCV 2022 Our method fuses multi-sensor depth streams regardless of time synchronization and calibration and generalizes well with little training data.

TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentation

TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentation

ECCV 2022 We introduce the more general taxonomy adaptive cross-domain semantic segmentation (TACS) problem, allowing for inconsistent taxonomies between the two domains.

Mask Transfiner for High-Quality Instance Segmentation

Mask Transfiner for High-Quality Instance Segmentation

CVPR 2022 we present Mask Transfiner for high-quality and efficient instance segmentation, which predicts highly accurate instance masks at a low computational cost using quadtree transformer.

SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation

SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation

CVPR 2022 We introduce the largest synthetic dataset for autonomous driving to study continuous domain adaptation and multi-task perception.

Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences

Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences

CVPR 2022 We propose Probabilistic Warp Consistency, a weakly-supervised learning objective for semantic matching.

Transforming Model Prediction for Tracking

Transforming Model Prediction for Tracking

CVPR 2022 We propose a tracker architecture employing a Transformer-based model prediction module.

Generative Cooperative Learning for Unsupervised Video Anomaly Detection

Generative Cooperative Learning for Unsupervised Video Anomaly Detection

CVPR 2022 Our method exploits the low frequency of anomalies towards building a cross-supervision between a generator and a discriminator.

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

CVPR 2022 We propose a Denoising Diffusion Probabilistic Model (DDPM) based inpainting approach that is applicable to even extreme masks.

LiDAR Snowfall Simulation for Robust 3D Object Detection

LiDAR Snowfall Simulation for Robust 3D Object Detection

CVPR 2022 Oral We propose a physically based method to simulate the effect of snowfall on real clear weather LiDAR point clouds.

On the Practicality of Deterministic Epistemic Uncertainty

On the Practicality of Deterministic Epistemic Uncertainty

ICML 2022 We provide a taxonomy of DUMs, evaluate their calibration under continuous distributional shifts, and extend them to semantic segmentation.

Fast Hierarchical Learning for Few-Shot Object Detection

Fast Hierarchical Learning for Few-Shot Object Detection

IROS 2022 We pose few-shot detection as a hierarchical learning problem, where the novel classes are treated as the child classes of existing base classes and the background class.

Monocular Quasi-Dense 3D Object Tracking

Monocular Quasi-Dense 3D Object Tracking

TPAMI 2022 We combine quasi-dense tracking on 2D images and motion prediction in 3D space to achieve significant advance in 3D object tracking from monocular videos.