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07/07/2023
Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification Segmentation
We address the task of weakly-supervised few-shot image classification a...
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06/20/2023
Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning
Learning to predict reliable characteristic orientations of 3D point clo...
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04/11/2023
Relational Context Learning for Human-Object Interaction Detection
Recent state-of-the-art methods for HOI detection typically build on tra...
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04/07/2023
Devil's on the Edges: Selective Quad Attention for Scene Graph Generation
Scene graph generation aims to construct a semantic graph structure from...
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03/25/2023
Learning Rotation-Equivariant Features for Visual Correspondence
Extracting discriminative local features that are invariant to imaging v...
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11/23/2022
Generalizable Implicit Neural Representations via Instance Pattern Composers
Despite recent advances in implicit neural representations (INRs), it re...
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11/14/2022
Few-shot Metric Learning: Online Adaptation of Embedding for Retrieval
Metric learning aims to build a distance metric typically by learning an...
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11/11/2022
Soft-Landing Strategy for Alleviating the Task Discrepancy Problem in Temporal Action Localization Tasks
Temporal Action Localization (TAL) methods typically operate on top of f...
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10/03/2022
Sequential Brick Assembly with Efficient Constraint Satisfaction
We address the problem of generating a sequence of LEGO brick assembly w...
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08/11/2022
Towards Sequence-Level Training for Visual Tracking
Despite the extensive adoption of machine learning on the task of visual...
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06/17/2022
Revisiting Self-Distillation
Knowledge distillation is the procedure of transferring "knowledge" from...
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06/15/2022
Self-Supervised Learning of Image Scale and Orientation
We study the problem of learning to assign a characteristic pose, i.e., ...
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06/14/2022
Peripheral Vision Transformer
Human vision possesses a special type of visual processing systems calle...
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06/09/2022
Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer
Although autoregressive models have achieved promising results on image ...
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05/27/2022
Future Transformer for Long-term Action Anticipation
The task of predicting future actions from a video is crucial for a real...
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05/24/2022
Learning to Assemble Geometric Shapes
Assembling parts into an object is a combinatorial problem that arises i...
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05/23/2022
TransforMatcher: Match-to-Match Attention for Semantic Correspondence
Establishing correspondences between images remains a challenging task, ...
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05/12/2022
Smooth-Reduce: Leveraging Patches for Improved Certified Robustness
Randomized smoothing (RS) has been shown to be a fast, scalable techniqu...
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05/04/2022
Self-Taught Metric Learning without Labels
We present a novel self-taught framework for unsupervised metric learnin...
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04/19/2022
Self-Supervised Equivariant Learning for Oriented Keypoint Detection
Detecting robust keypoints from an image is an integral part of many com...
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04/05/2022
Detector-Free Weakly Supervised Group Activity Recognition
Group activity recognition is the task of understanding the activity con...
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03/31/2022
Reflection and Rotation Symmetry Detection via Equivariant Learning
The inherent challenge of detecting symmetries stems from arbitrary orie...
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03/29/2022
Integrative Few-Shot Learning for Classification and Segmentation
We introduce the integrative task of few-shot classification and segment...
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03/03/2022
Autoregressive Image Generation using Residual Quantization
For autoregressive (AR) modeling of high-resolution images, vector quant...
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02/04/2022
Selective Network Linearization for Efficient Private Inference
Private inference (PI) enables inference directly on cryptographically s...
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01/17/2022
Contrastive Regularization for Semi-Supervised Learning
Consistency regularization on label predictions becomes a fundamental te...
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12/09/2021
Fast Point Transformer
The recent success of neural networks enables a better interpretation of...
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11/29/2021
Semi-supervised Domain Adaptation via Sample-to-Sample Self-Distillation
Semi-supervised domain adaptation (SSDA) is to adapt a learner to a new ...
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11/02/2021
Relational Self-Attention: What's Missing in Attention for Video Understanding
Convolution has been arguably the most important feature transform for m...
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11/01/2021
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training
Conditional Generative Adversarial Networks (cGAN) generate realistic im...
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10/29/2021
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
Discovering a solution in a combinatorial space is prevalent in many rea...
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10/04/2021
Differentiable Spline Approximations
The paradigm of differentiable programming has significantly enhanced th...
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09/11/2021
Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence
Despite advances in feature representation, leveraging geometric relatio...
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09/09/2021
Deep Hough Voting for Robust Global Registration
Point cloud registration is the task of estimating the rigid transformat...
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08/31/2021
Self-Calibrating Neural Radiance Fields
In this work, we propose a camera self-calibration algorithm for generic...
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08/30/2021
Learning to Discover Reflection Symmetry via Polar Matching Convolution
The task of reflection symmetry detection remains challenging due to sig...
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08/22/2021
Relational Embedding for Few-Shot Classification
We propose to address the problem of few-shot classification by meta-lea...
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06/17/2021
Sphynx: ReLU-Efficient Network Design for Private Inference
The emergence of deep learning has been accompanied by privacy concerns ...
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04/04/2021
Hypercorrelation Squeeze for Few-Shot Segmentation
Few-shot semantic segmentation aims at learning to segment a target obje...
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03/31/2021
Convolutional Hough Matching Networks
Despite advances in feature representation, leveraging geometric relatio...
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03/27/2021
Embedding Transfer with Label Relaxation for Improved Metric Learning
This paper presents a novel method for embedding transfer, a task of tra...
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02/14/2021
Learning Self-Similarity in Space and Time as Generalized Motion for Action Recognition
Spatio-temporal convolution often fails to learn motion dynamics in vide...
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11/26/2020
Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytope
Bayesian optimization is a popular method for solving the problem of glo...
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11/25/2020
CircleGAN: Generative Adversarial Learning across Spherical Circles
We present a novel discriminator for GANs that improves realness and div...
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09/09/2020
Diversified Mutual Learning for Deep Metric Learning
Mutual learning is an ensemble training strategy to improve generalizati...
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07/21/2020
Learning to Compose Hypercolumns for Visual Correspondence
Feature representation plays a crucial role in visual correspondence, an...
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07/20/2020
MotionSqueeze: Neural Motion Feature Learning for Video Understanding
Motion plays a crucial role in understanding videos and most state-of-th...
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07/13/2020
IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos
Most current action recognition methods heavily rely on appearance infor...
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07/07/2020
Hyperparameter Optimization in Neural Networks via Structured Sparse Recovery
In this paper, we study two important problems in the automated design o...
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06/28/2020