activity
20162026
most citedHands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users

891 citations · 1.1k across the 27 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

5 papers · 2 filters

cs.CV2024★ 2 cited

UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation

Chengyuan Zhang, Yilin Zhang, Lei Zhu +6

This paper introduces a novel framework for unified incremental few-shot object detection (iFSOD) and instance segmentation (iFSIS) using the Transformer architecture. Our goal is…

cs.CV2024

A Riemannian Approach for Spatiotemporal Analysis and Generation of 4D Tree-shaped Structures

Tahmina Khanam, Hamid Laga, Mohammed Bennamoun +5

We propose the first comprehensive approach for modeling and analyzing the spatiotemporal shape variability in tree-like 4D objects, i.e., 3D objects whose shapes bend, stretch, an…

cs.CV2024★ 1 cited

Faster Image2Video Generation: A Closer Look at CLIP Image Embedding's Impact on Spatio-Temporal Cross-Attentions

Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +4

This paper investigates the role of CLIP image embeddings within the Stable Video Diffusion (SVD) framework, focusing on their impact on video generation quality and computational…

cs.CV2024

Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation

Lian Xu, Mohammed Bennamoun, Farid Boussaid +3

Most existing weakly supervised semantic segmentation (WSSS) methods rely on Class Activation Mapping (CAM) to extract coarse class-specific localization maps using image-level lab…

cs.CV2024

Box It to Bind It: Unified Layout Control and Attribute Binding in T2I Diffusion Models

Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +3

While latent diffusion models (LDMs) excel at creating imaginative images, they often lack precision in semantic fidelity and spatial control over where objects are generated. To a…