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08/25/2023
Fine-tuning can cripple your foundation model; preserving features may be the solution
Pre-trained foundation models, owing primarily to their enormous capacit...
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06/07/2023
Faithful Knowledge Distillation
Knowledge distillation (KD) has received much attention due to its succe...
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05/16/2023
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?
We revisit the common practice of evaluating adaptation of Online Contin...
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04/25/2023
Certifying Ensembles: A General Certification Theory with S-Lipschitzness
Improving and guaranteeing the robustness of deep learning models has be...
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04/16/2023
Fairness in AI and Its Long-Term Implications on Society
Successful deployment of artificial intelligence (AI) in various setting...
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03/23/2023
Don't FREAK Out: A Frequency-Inspired Approach to Detecting Backdoor Poisoned Samples in DNNs
In this paper we investigate the frequency sensitivity of Deep Neural Ne...
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03/20/2023
Computationally Budgeted Continual Learning: What Does Matter?
Continual Learning (CL) aims to sequentially train models on streams of ...
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03/11/2023
Semantics-Aware Dynamic Localization and Refinement for Referring Image Segmentation
Referring image segmentation segments an image from a language expressio...
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03/03/2023
MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices
High-quality 3D ground-truth shapes are critical for 3D object reconstru...
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02/02/2023
Real-Time Evaluation in Online Continual Learning: A New Paradigm
Current evaluations of Continual Learning (CL) methods typically assume ...
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11/27/2022
Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs
Classifiers and generators have long been separated. We break down this ...
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11/12/2022
Bipartite Graph Reasoning GANs for Person Pose and Facial Image Synthesis
We present a novel bipartite graph reasoning Generative Adversarial Netw...
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11/12/2022
Structure-Preserving 3D Garment Modeling with Neural Sewing Machines
3D Garment modeling is a critical and challenging topic in the area of c...
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10/24/2022
Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning
This paper presents Holistically-Attracted Wireframe Parsing (HAWP) for ...
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09/24/2022
Learn what matters: cross-domain imitation learning with task-relevant embeddings
We study how an autonomous agent learns to perform a task from demonstra...
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09/24/2022
Raising the Bar on the Evaluation of Out-of-Distribution Detection
In image classification, a lot of development has happened in detecting ...
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09/20/2022
Dynamic Graph Message Passing Networks for Visual Recognition
Modelling long-range dependencies is critical for scene understanding ta...
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08/15/2022
Memory-Driven Text-to-Image Generation
We introduce a memory-driven semi-parametric approach to text-to-image g...
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07/22/2022
An Impartial Take to the CNN vs Transformer Robustness Contest
Following the surge of popularity of Transformers in Computer Vision, se...
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07/20/2022
Illusionary Attacks on Sequential Decision Makers and Countermeasures
Autonomous intelligent agents deployed to the real-world need to be robu...
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07/13/2022
Sample-dependent Adaptive Temperature Scaling for Improved Calibration
It is now well known that neural networks can be wrong with high confide...
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07/05/2022
SiamMask: A Framework for Fast Online Object Tracking and Segmentation
In this paper we introduce SiamMask, a framework to perform both visual ...
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06/29/2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness
We show that the effectiveness of the well celebrated Mixup [Zhang et al...
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06/17/2022
How robust are pre-trained models to distribution shift?
The vulnerability of machine learning models to spurious correlations ha...
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06/16/2022
Catastrophic overfitting is a bug but also a feature
Despite clear computational advantages in building robust neural network...
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04/25/2022
Zero-Shot Logit Adjustment
Semantic-descriptor-based Generalized Zero-Shot Learning (GZSL) poses ch...
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04/24/2022
Towards the Semantic Weak Generalization Problem in Generative Zero-Shot Learning: Ante-hoc and Post-hoc
In this paper, we present a simple and effective strategy lowering the p...
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04/03/2022
BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusion
Dense 3D reconstruction from a stream of depth images is the key to many...
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02/28/2022
Local and Global GANs with Semantic-Aware Upsampling for Image Generation
In this paper, we address the task of semantic-guided image generation. ...
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02/02/2022
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training
Recently, Wong et al. showed that adversarial training with single-step ...
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01/31/2022
Learning to Hash Naturally Sorts
Locality sensitive hashing pictures a list-wise sorting problem. Its tes...
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01/31/2022
Adversarial Masking for Self-Supervised Learning
We propose ADIOS, a masked image model (MIM) framework for self-supervis...
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01/31/2022
On the Robustness of Quality Measures for GANs
This work evaluates the robustness of quality measures of generative mod...
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12/04/2021
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
Referring image segmentation is a fundamental vision-language task that ...
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11/23/2021
Fixed Points in Cyber Space: Rethinking Optimal Evasion Attacks in the Age of AI-NIDS
Cyber attacks are increasing in volume, frequency, and complexity. In re...
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11/15/2021
Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge
Although deep learning methods have achieved advanced video object recog...
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10/29/2021
Deep Deterministic Uncertainty for Semantic Segmentation
We extend Deep Deterministic Uncertainty (DDU), a method for uncertainty...
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10/06/2021
Detecting and Quantifying Malicious Activity with Simulation-based Inference
We propose the use of probabilistic programming techniques to tackle the...
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09/11/2021
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques
Deep neural networks (DNNs) are vulnerable to adversarial noises, which ...
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07/09/2021
ANCER: Anisotropic Certification via Sample-wise Volume Maximization
Randomized smoothing has recently emerged as an effective tool that enab...
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07/05/2021
Do Different Tracking Tasks Require Different Appearance Models?
Tracking objects of interest in a video is one of the most popular and w...
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07/02/2021
DeformRS: Certifying Input Deformations with Randomized Smoothing
Deep neural networks are vulnerable to input deformations in the form of...
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06/23/2021
Learning Multimodal VAEs through Mutual Supervision
Multimodal VAEs seek to model the joint distribution over heterogeneous ...
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06/14/2021
KL Guided Domain Adaptation
Domain adaptation is an important problem and often needed for real-worl...
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06/03/2021
You Never Cluster Alone
Recent advances in self-supervised learning with instance-level contrast...
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04/20/2021
Gradient Matching for Domain Generalization
Machine learning systems typically assume that the distributions of trai...
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04/14/2021
Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition
We improve the scalability of Branch and Bound (BaB) algorithms for form...
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04/12/2021
Cloth Interactive Transformer for Virtual Try-On
2D image-based virtual try-on has attracted increased attention from the...
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03/26/2021
Combating Adversaries with Anti-Adversaries
Deep neural networks are vulnerable to small input perturbations known a...
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02/23/2021
