Search Results for author: Nuno Vasconcelos

Found 100 papers, 35 papers with code

SPOT: Selective Point Cloud Voting for Better Proposal in Point Cloud Object Detection

no code implementations ECCV 2020 Hongyuan Du, Linjun Li, Bo Liu, Nuno Vasconcelos

The sparsity of point clouds limits deep learning models on capturing long-range dependencies, which makes features extracted by the models ambiguous.

Object object-detection +1

Adapting Dual-encoder Vision-language Models for Paraphrased Retrieval

no code implementations6 May 2024 Jiacheng Cheng, Hijung Valentina Shin, Nuno Vasconcelos, Bryan Russell, Fabian Caba Heilbron

In this work, we consider the task of paraphrased text-to-image retrieval where a model aims to return similar results given a pair of paraphrased queries.

Image Retrieval Language Modelling +5

Editable Image Elements for Controllable Synthesis

no code implementations24 Apr 2024 Jiteng Mu, Michaël Gharbi, Richard Zhang, Eli Shechtman, Nuno Vasconcelos, Xiaolong Wang, Taesung Park

In this work, we propose an image representation that promotes spatial editing of input images using a diffusion model.

Long-Tailed Anomaly Detection with Learnable Class Names

no code implementations29 Mar 2024 Chih-Hui Ho, Kuan-Chuan Peng, Nuno Vasconcelos

Phase 2 then learns the parameters of the reconstruction and classification modules of LTAD.

Anomaly Detection

Diffusion-based Data Augmentation for Object Counting Problems

no code implementations25 Jan 2024 Zhen Wang, Yuelei Li, Jia Wan, Nuno Vasconcelos

Our proposed smoothed density map input for ControlNet significantly improves ControlNet's performance in generating crowds in the correct locations.

Crowd Counting Data Augmentation +2

SCHEME: Scalable Channer Mixer for Vision Transformers

no code implementations1 Dec 2023 Deepak Sridhar, Yunsheng Li, Nuno Vasconcelos

Vision Transformers have received significant attention due to their impressive performance in many vision tasks.

Image Classification object-detection +2

POP: Prompt Of Prompts for Continual Learning

no code implementations14 Jun 2023 Zhiyuan Hu, Jiancheng Lyu, Dashan Gao, Nuno Vasconcelos

We show that a foundation model equipped with POP learning is able to outperform classic CL methods by a significant margin.

Continual Learning Open-Ended Question Answering

Single-Stage Visual Relationship Learning using Conditional Queries

no code implementations9 Jun 2023 Alakh Desai, Tz-Ying Wu, Subarna Tripathi, Nuno Vasconcelos

Research in scene graph generation (SGG) usually considers two-stage models, that is, detecting a set of entities, followed by combining them and labeling all possible relationships.

Decoder Graph Generation +2

ProTeCt: Prompt Tuning for Taxonomic Open Set Classification

1 code implementation4 Jun 2023 Tz-Ying Wu, Chih-Hui Ho, Nuno Vasconcelos

A new Prompt Tuning for Hierarchical Consistency (ProTeCt) technique is then proposed to calibrate classification across label set granularities.

Classification open-set classification

ActorsNeRF: Animatable Few-shot Human Rendering with Generalizable NeRFs

no code implementations ICCV 2023 Jiteng Mu, Shen Sang, Nuno Vasconcelos, Xiaolong Wang

While NeRF-based human representations have shown impressive novel view synthesis results, most methods still rely on a large number of images / views for training.

Novel View Synthesis

Dense Network Expansion for Class Incremental Learning

no code implementations CVPR 2023 Zhiyuan Hu, Yunsheng Li, Jiancheng Lyu, Dashan Gao, Nuno Vasconcelos

This is accomplished by the introduction of dense connections between the intermediate layers of the task expert networks, that enable the transfer of knowledge from old to new tasks via feature sharing and reusing.

Class Incremental Learning Incremental Learning

Toward Unsupervised Realistic Visual Question Answering

no code implementations ICCV 2023 Yuwei Zhang, Chih-Hui Ho, Nuno Vasconcelos

To resolve the first drawback, we propose a new testing dataset, RGQA, which combines AQs from an existing VQA dataset with around 29K human-annotated UQs.

Question Answering Visual Question Answering

Towards Professional Level Crowd Annotation of Expert Domain Data

no code implementations CVPR 2023 Pei Wang, Nuno Vasconcelos

A new approach, based on semi-supervised learning (SSL) and denoted as SSL with human filtering (SSL-HF) is proposed.

DISCO: Adversarial Defense with Local Implicit Functions

1 code implementation11 Dec 2022 Chih-Hui Ho, Nuno Vasconcelos

The problem of adversarial defenses for image classification, where the goal is to robustify a classifier against adversarial examples, is considered.

Adversarial Defense Image Classification

YORO -- Lightweight End to End Visual Grounding

1 code implementation15 Nov 2022 Chih-Hui Ho, Srikar Appalaraju, Bhavan Jasani, R. Manmatha, Nuno Vasconcelos

We present YORO - a multi-modal transformer encoder-only architecture for the Visual Grounding (VG) task.

Natural Language Queries Visual Grounding

Should All Proposals be Treated Equally in Object Detection?

1 code implementation7 Jul 2022 Yunsheng Li, Yinpeng Chen, Xiyang Dai, Dongdong Chen, Mengchen Liu, Pei Yu, Jing Yin, Lu Yuan, Zicheng Liu, Nuno Vasconcelos

We formulate this as a learning problem where the goal is to assign operators to proposals, in the detection head, so that the total computational cost is constrained and the precision is maximized.

Object Object Detection

Meta-Learning over Time for Destination Prediction Tasks

no code implementations29 Jun 2022 Mark Tenzer, Zeeshan Rasheed, Khurram Shafique, Nuno Vasconcelos

A need to understand and predict vehicles' behavior underlies both public and private goals in the transportation domain, including urban planning and management, ride-sharing services, and intelligent transportation systems.

Management Meta-Learning

VALHALLA: Visual Hallucination for Machine Translation

1 code implementation CVPR 2022 Yi Li, Rameswar Panda, Yoon Kim, Chun-Fu, Chen, Rogerio Feris, David Cox, Nuno Vasconcelos

In particular, given a source sentence an autoregressive hallucination transformer is used to predict a discrete visual representation from the input text, and the combined text and hallucinated representations are utilized to obtain the target translation.

Hallucination Multimodal Machine Translation +2

Class-Incremental Learning with Strong Pre-trained Models

1 code implementation CVPR 2022 Tz-Ying Wu, Gurumurthy Swaminathan, Zhizhong Li, Avinash Ravichandran, Nuno Vasconcelos, Rahul Bhotika, Stefano Soatto

We hypothesize that a strong base model can provide a good representation for novel classes and incremental learning can be done with small adaptations.

Class Incremental Learning Incremental Learning

Omni-DETR: Omni-Supervised Object Detection with Transformers

1 code implementation CVPR 2022 Pei Wang, Zhaowei Cai, Hao Yang, Gurumurthy Swaminathan, Nuno Vasconcelos, Bernt Schiele, Stefano Soatto

This is enabled by a unified architecture, Omni-DETR, based on the recent progress on student-teacher framework and end-to-end transformer based object detection.

Object object-detection +2

CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs

1 code implementation CVPR 2022 Jiteng Mu, Shalini De Mello, Zhiding Yu, Nuno Vasconcelos, Xiaolong Wang, Jan Kautz, Sifei Liu

We represent the correspondence maps of different images as warped coordinate frames transformed from a canonical coordinate frame, i. e., the correspondence map, which describes the structure (e. g., the shape of a face), is controlled via a transformation.

Disentanglement

Calibrating Deep Neural Networks by Pairwise Constraints

no code implementations CVPR 2022 Jiacheng Cheng, Nuno Vasconcelos

This suggests the hypothesis that DNN calibration can be improved by providing calibration supervision to all such binary problems.

Binary Classification

Improving Video Model Transfer With Dynamic Representation Learning

no code implementations CVPR 2022 Yi Li, Nuno Vasconcelos

DRL is then formulated as an adversarial learning problem between the video and spatial models, with the objective of maximizing the dynamic score of learned spatiotemporal classifier.

Action Classification Knowledge Distillation +4

BEV-Net: Assessing Social Distancing Compliance by Joint People Localization and Geometric Reasoning

1 code implementation ICCV 2021 Zhirui Dai, Yuepeng Jiang, Yi Li, Bo Liu, Antoni B. Chan, Nuno Vasconcelos

A dataset of crowd scenes with people annotations under a bird's eye view (BEV) and ground truth for metric distances is introduced, and several measures for the evaluation of social distance detection systems are proposed.

Pose Estimation

OOWL500: Overcoming Dataset Collection Bias in the Wild

no code implementations24 Aug 2021 Brandon Leung, Chih-Hui Ho, Amir Persekian, David Orozco, Yen Chang, Erik Sandstrom, Bo Liu, Nuno Vasconcelos

Second, it is used to show that the augmentation of in the wild datasets, such as ImageNet, with in the lab data, such as OOWL500, can significantly decrease these biases, leading to object recognizers of improved generalization.

Adversarial Attack Data Augmentation +2

Black-Box Test-Time Shape REFINEment for Single View 3D Reconstruction

no code implementations23 Aug 2021 Brandon Leung, Chih-Hui Ho, Nuno Vasconcelos

Much recent progress has been made in reconstructing the 3D shape of an object from an image of it, i. e. single view 3D reconstruction.

3D Reconstruction Single-View 3D Reconstruction

MicroNet: Improving Image Recognition with Extremely Low FLOPs

1 code implementation ICCV 2021 Yunsheng Li, Yinpeng Chen, Xiyang Dai, Dongdong Chen, Mengchen Liu, Lu Yuan, Zicheng Liu, Lei Zhang, Nuno Vasconcelos

This paper aims at addressing the problem of substantial performance degradation at extremely low computational cost (e. g. 5M FLOPs on ImageNet classification).

Gradient-Based Algorithms for Machine Teaching

no code implementations CVPR 2021 Pei Wang, Kabir Nagrecha, Nuno Vasconcelos

This is formulated as a problem of functional optimization where, at each teaching iteration, the teacher seeks to align the steepest descent directions of the risk of (1) the teaching set and (2) entire example population.

BIG-bench Machine Learning

Breadcrumbs: Adversarial Class-Balanced Sampling for Long-tailed Recognition

no code implementations1 May 2021 Bo Liu, Haoxiang Li, Hao Kang, Gang Hua, Nuno Vasconcelos

It is shown that, unlike class-balanced sampling, this is an adversarial augmentation strategy.

Semi-supervised Long-tailed Recognition using Alternate Sampling

no code implementations1 May 2021 Bo Liu, Haoxiang Li, Hao Kang, Nuno Vasconcelos, Gang Hua

A consistency loss has been introduced to limit the impact from unlabeled data while leveraging them to update the feature embedding.

GistNet: a Geometric Structure Transfer Network for Long-Tailed Recognition

no code implementations ICCV 2021 Bo Liu, Haoxiang Li, Hao Kang, Gang Hua, Nuno Vasconcelos

A new learning algorithm is then proposed for GeometrIc Structure Transfer (GIST), with resort to a combination of loss functions that combine class-balanced and random sampling to guarantee that, while overfitting to the popular classes is restricted to geometric parameters, it is leveraged to transfer class geometry from popular to few-shot classes.

Transfer Learning

Sparse Pose Trajectory Completion

no code implementations1 May 2021 Bo Liu, Mandar Dixit, Roland Kwitt, Gang Hua, Nuno Vasconcelos

In the absence of dense pose sampling in image space, these latent space trajectories provide cross-modal guidance for learning.

Novel View Synthesis Object

A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation

1 code implementation ICCV 2021 Jiteng Mu, Weichao Qiu, Adam Kortylewski, Alan Yuille, Nuno Vasconcelos, Xiaolong Wang

To deal with the large shape variance, we introduce Articulated Signed Distance Functions (A-SDF) to represent articulated shapes with a disentangled latent space, where we have separate codes for encoding shape and articulation.

Test-time Adaptation

IMAGINE: Image Synthesis by Image-Guided Model Inversion

no code implementations CVPR 2021 Pei Wang, Yijun Li, Krishna Kumar Singh, Jingwan Lu, Nuno Vasconcelos

We introduce an inversion based method, denoted as IMAge-Guided model INvErsion (IMAGINE), to generate high-quality and diverse images from only a single training sample.

Image Generation Specificity

Rethinking and Improving the Robustness of Image Style Transfer

1 code implementation CVPR 2021 Pei Wang, Yijun Li, Nuno Vasconcelos

Extensive research in neural style transfer methods has shown that the correlation between features extracted by a pre-trained VGG network has a remarkable ability to capture the visual style of an image.

Style Transfer

Robust Audio-Visual Instance Discrimination

no code implementations CVPR 2021 Pedro Morgado, Ishan Misra, Nuno Vasconcelos

Second, since self-supervised contrastive learning relies on random sampling of negative instances, instances that are semantically similar to the base instance can be used as faulty negatives.

Action Recognition Contrastive Learning +2

Dynamic Transfer for Multi-Source Domain Adaptation

1 code implementation CVPR 2021 Yunsheng Li, Lu Yuan, Yinpeng Chen, Pei Wang, Nuno Vasconcelos

However, such a static model is difficult to handle conflicts across multiple domains, and suffers from a performance degradation in both source domains and target domain.

Domain Adaptation

Revisiting Dynamic Convolution via Matrix Decomposition

1 code implementation ICLR 2021 Yunsheng Li, Yinpeng Chen, Xiyang Dai, Mengchen Liu, Dongdong Chen, Ye Yu, Lu Yuan, Zicheng Liu, Mei Chen, Nuno Vasconcelos

It has two limitations: (a) it increases the number of convolutional weights by K-times, and (b) the joint optimization of dynamic attention and static convolution kernels is challenging.

Dimensionality Reduction

A Machine Teaching Framework for Scalable Recognition

no code implementations ICCV 2021 Pei Wang, Nuno Vasconcelos

Preliminary studies show that the accuracy of classifiers trained on the final dataset is a function of the accuracy of the student annotators.

counterfactual Self-Supervised Learning

MicroNet: Towards Image Recognition with Extremely Low FLOPs

no code implementations24 Nov 2020 Yunsheng Li, Yinpeng Chen, Xiyang Dai, Dongdong Chen, Mengchen Liu, Lu Yuan, Zicheng Liu, Lei Zhang, Nuno Vasconcelos

In this paper, we present MicroNet, which is an efficient convolutional neural network using extremely low computational cost (e. g. 6 MFLOPs on ImageNet classification).

Learning Representations from Audio-Visual Spatial Alignment

no code implementations NeurIPS 2020 Pedro Morgado, Yi Li, Nuno Vasconcelos

To learn from these spatial cues, we tasked a network to perform contrastive audio-visual spatial alignment of 360{\deg} video and spatial audio.

Action Recognition Representation Learning +2

Contrastive Learning with Adversarial Examples

no code implementations NeurIPS 2020 Chih-Hui Ho, Nuno Vasconcelos

This paper addresses the problem, by introducing a new family of adversarial examples for constrastive learning and using these examples to define a new adversarial training algorithm for SSL, denoted as CLAE.

Contrastive Learning Self-Supervised Learning

Deep Hashing with Hash-Consistent Large Margin Proxy Embeddings

no code implementations27 Jul 2020 Pedro Morgado, Yunsheng Li, Jose Costa Pereira, Mohammad Saberian, Nuno Vasconcelos

The use of a fixed set of proxies (weights of the CNN classification layer) is proposed to eliminate this ambiguity, and a procedure to design proxy sets that are nearly optimal for both classification and hashing is introduced.

Binarization Classification +2

Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier

1 code implementation ECCV 2020 Tz-Ying Wu, Pedro Morgado, Pei Wang, Chih-Hui Ho, Nuno Vasconcelos

Motivated by this, a deep realistic taxonomic classifier (Deep-RTC) is proposed as a new solution to the long-tail problem, combining realism with hierarchical predictions.

Few-Shot Open-Set Recognition using Meta-Learning

1 code implementation CVPR 2020 Bo Liu, Hao Kang, Haoxiang Li, Gang Hua, Nuno Vasconcelos

It is argued that the classic softmax classifier is a poor solution for open-set recognition, since it tends to overfit on the training classes.

Classification General Classification +3

SCOUT: Self-aware Discriminant Counterfactual Explanations

2 code implementations CVPR 2020 Pei Wang, Nuno Vasconcelos

It is argued that self-awareness, namely the ability to produce classification confidence scores, is important for the computation of discriminant explanations, which seek to identify regions where it is easy to discriminate between prediction and counter class.

Attribute counterfactual

Rethinking Differentiable Search for Mixed-Precision Neural Networks

2 code implementations CVPR 2020 Zhaowei Cai, Nuno Vasconcelos

Low-precision networks, with weights and activations quantized to low bit-width, are widely used to accelerate inference on edge devices.

Combinatorial Optimization

Exploit Clues from Views: Self-Supervised and Regularized Learning for Multiview Object Recognition

1 code implementation CVPR 2020 Chih-Hui Ho, Bo Liu, Tz-Ying Wu, Nuno Vasconcelos

Multiview recognition has been well studied in the literature and achieves decent performance in object recognition and retrieval task.

Object Object Recognition +2

NetTailor: Tuning the Architecture, Not Just the Weights

1 code implementation CVPR 2019 Pedro Morgado, Nuno Vasconcelos

Under the standard paradigm of network fine-tuning, an entirely new CNN is learned per task, and the final network size is independent of task complexity.

Continual Learning Object Recognition +2

Efficient Multi-Domain Network Learning by Covariance Normalization

no code implementations24 Jun 2019 Yunsheng Li, Nuno Vasconcelos

The problem of multi-domain learning of deep networks is considered.

Cascade R-CNN: High Quality Object Detection and Instance Segmentation

4 code implementations24 Jun 2019 Zhaowei Cai, Nuno Vasconcelos

In object detection, the intersection over union (IoU) threshold is frequently used to define positives/negatives.

Instance Segmentation object-detection +3

Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes

no code implementations27 May 2019 Mandar Dixit, Yunsheng Li, Nuno Vasconcelos

Somewhat surprisingly, the scene classification results are superior to those of a CNN explicitly trained for scene classification, using a large scene dataset (Places).

Classification General Classification +2

REPAIR: Removing Representation Bias by Dataset Resampling

1 code implementation CVPR 2019 Yi Li, Nuno Vasconcelos

An experimental set-up is also introduced to measure the bias of any dataset for a given representation, and the impact of this bias on the performance of recognition models.

Action Recognition Temporal Action Localization

Towards Universal Object Detection by Domain Attention

1 code implementation CVPR 2019 Xudong Wang, Zhaowei Cai, Dashan Gao, Nuno Vasconcelos

Experiments, on a newly established universal object detection benchmark of 11 diverse datasets, show that the proposed detector outperforms a bank of individual detectors, a multi-domain detector, and a baseline universal detector, with a 1. 3x parameter increase over a single-domain baseline detector.

Object object-detection +1

Super Diffusion for Salient Object Detection

no code implementations22 Nov 2018 Peng Jiang, Zhiyi Pan, Nuno Vasconcelos, Baoquan Chen, Jingliang Peng

Following this analysis, we propose super diffusion, a novel inclusive learning-based framework for salient object detection, which makes the optimum and robust performance by integrating a large pool of feature spaces, scales and even features originally computed for non-diffusion-based salient object detection.

Clustering Object +3

Self-Supervised Generation of Spatial Audio for 360 Video

1 code implementation7 Sep 2018 Pedro Morgado, Nuno Vasconcelos, Timothy Langlois, Oliver Wang

Using our approach, we show that it is possible to infer the spatial location of sound sources based only on 360 video and a mono audio track.

Towards Realistic Predictors

no code implementations ECCV 2018 Pei Wang, Nuno Vasconcelos

It is argued that this should be a predictor independent of the classifier itself, but tuned to it, and learned without explicit supervision, so as to learn from its mistakes.

Feature Space Transfer for Data Augmentation

no code implementations CVPR 2018 Bo Liu, Xudong Wang, Mandar Dixit, Roland Kwitt, Nuno Vasconcelos

A new architecture, denoted the FeATure TransfEr Network (FATTEN), is proposed for the modeling of feature trajectories induced by variations of object pose.

Data Augmentation Decoder +3

Cascade R-CNN: Delving into High Quality Object Detection

8 code implementations CVPR 2018 Zhaowei Cai, Nuno Vasconcelos

In object detection, an intersection over union (IoU) threshold is required to define positives and negatives.

Object Object Detection +1

AGA: Attribute-Guided Augmentation

1 code implementation CVPR 2017 Mandar Dixit, Roland Kwitt, Marc Niethammer, Nuno Vasconcelos

We implement our approach as a deep encoder-decoder architecture that learns the synthesis function in an end-to-end manner.

Attribute Data Augmentation +4

AGA: Attribute Guided Augmentation

1 code implementation8 Dec 2016 Mandar Dixit, Roland Kwitt, Marc Niethammer, Nuno Vasconcelos

We implement our approach as a deep encoder-decoder architecture that learns the synthesis function in an end-to-end manner.

Attribute Data Augmentation +4

Object based Scene Representations using Fisher Scores of Local Subspace Projections

no code implementations NeurIPS 2016 Mandar D. Dixit, Nuno Vasconcelos

While this problem is currently addressed with Fisher vector representations, these are now shown ineffective for the high-dimensional and highly non-linear features extracted by modern CNNs.

Scene Classification

Peak-Piloted Deep Network for Facial Expression Recognition

no code implementations24 Jul 2016 Xiangyun Zhao, Xiaodan Liang, Luoqi Liu, Teng Li, Yugang Han, Nuno Vasconcelos, Shuicheng Yan

Objective functions for training of deep networks for face-related recognition tasks, such as facial expression recognition (FER), usually consider each sample independently.

Face Recognition Facial Expression Recognition +2

VLAD3: Encoding Dynamics of Deep Features for Action Recognition

no code implementations CVPR 2016 Yingwei Li, Weixin Li, Vijay Mahadevan, Nuno Vasconcelos

To account for long-range inhomogeneous dynamics, a VLAD descriptor is derived for the LDS and pooled over the whole video, to arrive at the final VLAD^3 representation.

Action Recognition Temporal Action Localization

Bayesian Model Adaptation for Crowd Counts

no code implementations ICCV 2015 Bo Liu, Nuno Vasconcelos

A large video dataset for the evaluation of adaptation approaches to crowd counting is also introduced.

Crowd Counting Gaussian Processes +1

Generic Promotion of Diffusion-Based Salient Object Detection

no code implementations ICCV 2015 Peng Jiang, Nuno Vasconcelos, Jingliang Peng

In this work, we propose a generic scheme to promote any diffusion-based salient object detection algorithm by original ways to re-synthesize the diffusion matrix and construct the seed vector.

Clustering Object +3

Learning Complexity-Aware Cascades for Deep Pedestrian Detection

no code implementations ICCV 2015 Zhaowei Cai, Mohammad Saberian, Nuno Vasconcelos

CompACT cascades are shown to seek an optimal trade-off between accuracy and complexity by pushing features of higher complexity to the later cascade stages, where only a few difficult candidate patches remain to be classified.

Pedestrian Detection

Multiple Instance Learning for Soft Bags via Top Instances

no code implementations CVPR 2015 Weixin Li, Nuno Vasconcelos

Under this formulation, both positive and negative bags are soft, in the sense that negative bags can also contain positive instances.

Multiple Instance Learning

Parametric Regression on the Grassmannian

no code implementations14 May 2015 Yi Hong, Nikhil Singh, Roland Kwitt, Nuno Vasconcelos, Marc Niethammer

We then specialize this idea to the Grassmann manifold and demonstrate that it yields a simple, extensible and easy-to-implement solution to the parametric regression problem.

Crowd Counting regression

Learning Optimal Seeds for Diffusion-based Salient Object Detection

no code implementations CVPR 2014 Song Lu, Vijay Mahadevan, Nuno Vasconcelos

The propagation of the resulting saliency seeds, using a diffusion process, is finally shown to outperform the state of the art on a number of salient object detection datasets.

Object object-detection +4

Recognizing Activities via Bag of Words for Attribute Dynamics

no code implementations CVPR 2013 Weixin Li, Qian Yu, Harpreet Sawhney, Nuno Vasconcelos

A video sequence is decomposed into short-term segments, which are characterized by the dynamics of their attributes.

Activity Recognition Attribute

Cost-Sensitive Support Vector Machines

1 code implementation5 Dec 2012 Hamed Masnadi-Shirazi, Nuno Vasconcelos, Arya Iranmehr

Minimization of the new hinge loss is shown to be a generalization of the classic SVM optimization problem, and can be solved by identical procedures.

General Classification

Recognizing Activities by Attribute Dynamics

no code implementations NeurIPS 2012 Weixin Li, Nuno Vasconcelos

The proposed method is shown to outperform similar classifiers derived from the kernel dynamic system (KDS) and state-of-the-art approaches for dynamics-based or attribute-based action recognition.

Action Recognition Attribute +1

Multiclass Boosting: Theory and Algorithms

no code implementations NeurIPS 2011 Mohammad J. Saberian, Nuno Vasconcelos

Two algorithms are proposed: 1) CD-MCBoost, based on coordinate descent, updates one predictor component at a time, 2) GD-MCBoost, based on gradient descent, updates all components jointly.

A biologically plausible network for the computation of orientation dominance

no code implementations NeurIPS 2010 Kritika Muralidharan, Nuno Vasconcelos

This leads to a novel measure for the dominance of a given orientation $\theta$, which is similar to that used by SIFT.

Object Recognition

Variable margin losses for classifier design

no code implementations NeurIPS 2010 Hamed Masnadi-Shirazi, Nuno Vasconcelos

It is shown that, when the risk is in canonical form and the link is inverse sigmoidal, the margin properties of the loss are determined by a single parameter.

General Classification

On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost

no code implementations NeurIPS 2008 Hamed Masnadi-Shirazi, Nuno Vasconcelos

This shows that the standard approach of proceeding from the specification of a loss, to the minimization of conditional risk is overly restrictive.

General Classification

The discriminant center-surround hypothesis for bottom-up saliency

no code implementations NeurIPS 2007 Dashan Gao, Vijay Mahadevan, Nuno Vasconcelos

The classical hypothesis, that bottom-up saliency is a center-surround process, is combined with a more recent hypothesis that all saliency decisions are optimal in a decision-theoretic sense.

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