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
CVPR 2023 We remove video and image mask annptation necessity for training highly accurate VIS models.
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
ICRA 2023 We present TrafficBots, a multi-agent policy built upon motion prediction and end-to-end driving.
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
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
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
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
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
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
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
ECCV 2022 We propose SAGA (StochAstic whole-body Grasping with contAct).
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
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
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
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
CVPR 2022 We propose Probabilistic Warp Consistency, a weakly-supervised learning objective for semantic matching.
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
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
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
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
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
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
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.