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08/31/2023
InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion
This paper addresses a novel task of anticipating 3D human-object intera...
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08/08/2023
An Empirical Analysis of Range for 3D Object Detection
LiDAR-based 3D detection plays a vital role in autonomous navigation. Su...
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08/03/2023
Revisiting Deformable Convolution for Depth Completion
Depth completion, which aims to generate high-quality dense depth maps f...
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07/28/2023
Semi-Supervised Object Detection in the Open World
Existing approaches for semi-supervised object detection assume a fixed ...
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06/24/2023
Is Pre-training Truly Better Than Meta-Learning?
In the context of few-shot learning, it is currently believed that a fix...
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06/08/2023
Stochastic Multi-Person 3D Motion Forecasting
This paper aims to deal with the ignored real-world complexities in prio...
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05/05/2023
DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception
Closing the domain gap between training and deployment and incorporating...
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05/04/2023
NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Clouds
This paper proposes NeuralEditor that enables neural radiance fields (Ne...
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05/04/2023
Contrastive Mean Teacher for Domain Adaptive Object Detectors
Object detectors often suffer from the domain gap between training (sour...
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03/27/2023
Object Discovery from Motion-Guided Tokens
Object discovery – separating objects from the background without manual...
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02/09/2023
Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors
Predicting diverse human motions given a sequence of historical poses ha...
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02/07/2023
Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking
This work proposes an end-to-end multi-camera 3D multi-object tracking (...
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10/27/2022
Do Pre-trained Models Benefit Equally in Continual Learning?
Existing work on continual learning (CL) is primarily devoted to develop...
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10/18/2022
CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with Demonstrations
Although reinforcement learning has found widespread use in dense reward...
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10/10/2022
Learning with an Evolving Class Ontology
Lifelong learners must recognize concept vocabularies that evolve over t...
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08/11/2022
PointTree: Transformation-Robust Point Cloud Encoder with Relaxed K-D Trees
Being able to learn an effective semantic representation directly on raw...
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08/02/2022
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence
Recently, it has been observed that a transfer learning solution might b...
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06/10/2022
Is Self-Supervised Learning More Robust Than Supervised Learning?
Self-supervised contrastive learning is a powerful tool to learn visual ...
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06/09/2022
Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields
Comprehensive 3D scene understanding, both geometrically and semanticall...
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03/27/2022
Long-Tailed Recognition via Weight Balancing
In the real open world, data tends to follow long-tailed class distribut...
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03/18/2022
Discovering Objects that Can Move
This paper studies the problem of object discovery – separating objects ...
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12/24/2021
Does MAML Only Work via Feature Re-use? A Data Centric Perspective
Recent work has suggested that a good embedding is all we need to solve ...
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12/24/2021
The Curse of Zero Task Diversity: On the Failure of Transfer Learning to Outperform MAML and their Empirical Equivalence
Recently, it has been observed that a transfer learning solution might b...
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12/13/2021
Embracing Single Stride 3D Object Detector with Sparse Transformer
In LiDAR-based 3D object detection for autonomous driving, the ratio of ...
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10/06/2021
On the Importance of Firth Bias Reduction in Few-Shot Classification
Learning accurate classifiers for novel categories from very few example...
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09/20/2021
On the Importance of Distractors for Few-Shot Classification
Few-shot classification aims at classifying categories of a novel task b...
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08/20/2021
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation
We present a novel semi-supervised semantic segmentation method which jo...
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06/25/2021
Generative Modeling for Multi-task Visual Learning
Generative modeling has recently shown great promise in computer vision,...
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05/04/2021
Hallucination Improves Few-Shot Object Detection
Learning to detect novel objects from few annotated examples is of great...
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04/12/2021
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Training on datasets with long-tailed distributions has been challenging...
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03/30/2021
DAP: Detection-Aware Pre-training with Weak Supervision
This paper presents a detection-aware pre-training (DAP) approach, which...
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11/19/2020
Cooperating RPN's Improve Few-Shot Object Detection
Learning to detect an object in an image from very few training examples...
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08/22/2020
Few-Shot Learning with Intra-Class Knowledge Transfer
We consider the few-shot classification task with an unbalanced dataset,...
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08/17/2020
Alpha Net: Adaptation with Composition in Classifier Space
Deep learning classification models typically train poorly on classes wi...
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08/16/2020
Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis
Generative modeling has recently shown great promise in computer vision,...
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05/21/2020
Towards Streaming Image Understanding
Embodied perception refers to the ability of an autonomous agent to perc...
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11/29/2019
Learning Generalizable Representations via Diverse Supervision
The problem of rare category recognition has received a lot of attention...
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07/18/2019
Growing a Brain: Fine-Tuning by Increasing Model Capacity
CNNs have made an undeniable impact on computer vision through the abili...
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05/28/2019
Image Deformation Meta-Networks for One-Shot Learning
Humans can robustly learn novel visual concepts even when images undergo...
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12/21/2018
Learning Compositional Representations for Few-Shot Recognition
One of the key limitations of modern deep learning based approaches lies...
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01/16/2018
